Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball patterned arrays Spatially resolved transcriptomic technologies are promising tools to study cell fate decisions in a physical microenvironment, which is fundamental for enhancing our knowledge of mammalian development. However, the imbalance between resolution, transcript capture and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation mammalian embryos. Here, we combined DNA nanoball (DNB) patterned arrays and tissue RNA capture to create SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq). This approach allows transcriptomic profiling of large histological sections with high resolution and sensitivity. We have applied Stereo-seq to study the kinetics and directionality of transcriptional variation in a time course of mouse organogenesis. We used this information to gain insight into the molecular basis of regional specification, neuronal migration and differentiation in the developing brain. Furthermore, we mapped the expression of a panel of developmental disease-related loci on our global transcriptomic maps to define the spatiotemporal windows of tissue vulnerability. Our panoramic atlas constitutes an essential resource to investigate longstanding questions concerning normal and abnormal mammalian development.
α-Phenylalanyl tRNA synthetase competes with Notch signaling through its N-terminal domain The alpha subunit of the cytoplasmic Phenylalanyl tRNA synthetase (-PheRS, FARSA in humans) displays cell growth and proliferation activities and its elevated levels can induce cell fate changes and tumor-like phenotypes that do neither dependent on the canonical function of charging tRNAPhe with phenylalanine nor on stimulating general translation. In intestinal stem cells of Drosophila midguts, -PheRS levels are naturally slightly elevated and human FARSA mRNA levels are elevated in multiple cancers. In the Drosophila midgut model, elevated -PheRS levels caused the accumulation of many additional proliferating cells resembling intestinal stem cells (ISCs) and enteroblasts (EBs). This phenotype resembles partially the tumor-like phenotype described as Notch RNAi phenotype for the same cells. Genetic interactions between -PheRS and Notch suggest that their activities neutralize each other and that elevated -PheRS levels attenuate Notch signaling whether Notch induces differentiation into enterocytes, neuroblast stem cell proliferation, or transcription of a Notch reporter. These non-canonical functions all map to the N-terminal part of -PheRS which accumulates naturally in the intestine. This truncated version of -PheRS (-S) also localizes to nuclei and displays weak sequence similarity to the Notch intracellular domain (NICD), suggesting that -S might compete with the NICD for binding to a common target. Supporting this hypothesis, the tryptophan (W) residue reported to be key for the interaction between the NICD and the Su(H) BTD domain is not only conserved in -PheRS and -S, but also essential for attenuating Notch signaling.

Author SummaryAminoacyl tRNA synthetases charge tRNAs with their cognate amino acid to ensure proper decoding of the genetic code during translation. Independent of its aminoacylation function, the alpha subunit of Drosophila cytoplasmic Phenylalanyl tRNA synthetase (-PheRS, FARSA in humans) has an additional activity that promotes growth and proliferation (Ho et al., 2021). Here we describe that elevated -PheRS levels also induce cell fate changes and tumorous phenotypes in Drosophila midguts. Excessive proliferating cells with stem and progenitor cell characteristics accumulate and the composition of the terminally differentiated cells changes, too. This phenotype together with observed genetic interactions between -PheRS and Notch levels show that -PheRS counteracts Notch signaling in many different tissues and developmental stages. This novel activity of -PheRS maps to its N-terminal part, which is naturally produced. The fragment contains a DNA binding domain, translocates into nuclei, and displays essential similarities to a Notch domain that binds to the downstream transcription factor. This suggests that it might be competing with Notch for binding to a common target. Not only because Notch plays important roles in many tumors, but also because FARSA mRNA levels are considerably upregulated in many tumors, this novel activity deserves more attention for cancer research.
Short-term perceptual re-weighting in suprasegmental categorization Segmental speech units such as phonemes are cued by multiple acoustic dimensions (e.g. F0 and duration), but dimensions do not carry equal perceptual weight. The relative perceptual weights of acoustic speech dimensions are not fixed but vary with context. For example, when speech is altered to create an  accent in which two acoustic dimensions are correlated in a manner opposite that of long-term experience, the dimension that carries less perceptual weight is down-weighted to contribute less in category decisions. It remains unclear, however, whether this short-term reweighting is limited to segmental categorization, or if it extends to categorization of suprasegmental features which span multiple phonemes, syllables, or words, which would suggest that such "dimension-based statistical learning" is a widespread phenomenon in speech perception. Here we investigated the relative contribution of two acoustic dimensions to word emphasis. Participants categorized instances of a two-word phrase pronounced with typical covariation of fundamental frequency (F0) and duration, and in the context of an artificial  accent in which F0 and duration (established in prior research on English speech as  primary and  secondary dimensions, respectively) covaried atypically. When categorizing  accented speech, listeners rapidly down-weighted the secondary dimension (duration) while continuing to rely on the primary dimension (F0). This result indicates that listeners continually track short-term regularities across speech input and dynamically adjust the weight of acoustic evidence for suprasegmental categories. Thus, dimension-based statistical learning appears to be a widespread phenomenon in speech perception extending to both segmental and suprasegmental categorization. Targeting SARS-CoV-2 infection through CAR-T like bispecific T cell engagers incorporating ACE2 Despite advances in antibody treatments and vaccines, COVID-19 caused by SARS-CoV-2 infection remains a major health problem resulting in excessive morbidity and mortality and the emergence of new variants has reduced the effectiveness of current vaccines. Here, as a proof-of-concept we engineered primary CD8 T cells to express SARS-CoV-2 Spike protein-specific CARs, using extracellular region of ACE2, and demonstrated their highly specific and potent cytotoxicity towards Spike-expressing target cells. To improve on this concept as a potential therapeutic, we developed a bispecific T cell engager combining ACE2 with an anti-CD3 scFv (ACE2-Bite) to target infected cells and the virus. Similar to CAR-T cell approach, ACE2-Bite endowed cytotoxic cells to selectively kill Spike-expressing targets. Furthermore, ACE2-Bite neutralized the pseudoviruses of SARS-CoV, SARS-CoV-2 wild-type and variants including Delta and Omicron, as a decoy protein. Remarkably, ACE2-Bite molecule showed a higher binding and neutralization affinity to Delta and Omicron variants compared to SARS-CoV-2 wild-type Spike proteins, suggesting the potential of this approach as a variant-proof, therapeutic strategy for future SARS-CoV-2 variants, employing both humoral and cellular arms of the adaptive immune response. Heterogeneous mutation rates and spectra in yeast hybrids Mutation rates and spectra vary between species and among populations. Hybridization can contribute to this variation, but its role remains poorly understood. Estimating mutation rates requires controlled conditions where the effect of natural selection can be minimized. One way to achieve this is through mutation accumulation experiments coupled with genome sequencing. Here we investigate 400 mutation accumulation lines initiated from 11 genotypes spanning intra-lineage, inter-lineage and interspecific crosses of the yeasts Saccharomyces paradoxus and S. cerevisiae and propagated for 770 generations. We find significant differences in mutation rates and spectra among crosses, which are not related to the level of divergence of parental strains but are specific to some genotype combinations. Differences in number of generations and departures from neutrality play a minor role, whereas polyploidy and loss of heterozygosity impact mutation rates in some of the hybrid crosses in an opposite way. An integrative approach leads to the discovery of a novel anti-leukemic peptide from human milk Chemotherapy in childhood leukemia is associated with late morbidity in leukemic survivors, while certain patient subsets are relatively resistant to standard chemotherapy. It is therefore important to identify new agents with sensitivity and selectivity towards leukemic cells, while having less systemic toxicity. Peptide-based therapeutics has gained much attention during the last few years. Here, we used an integrative workflow combining mass spectrometric peptide library construction, in silico anticancer peptide screening, and in vitro leukemic cell studies to discover a novel anti-leukemic peptide having 3+charges and alpha-helical structure, namely HMP-S7, from human breast milk. HMP-S7 showed cytotoxic activity against four distinct leukemic cell lines in a dose-dependent manner but had no effect on solid malignancies or representative normal cells. HMP-S7 induced leukemic cell death by penetrating the plasma membrane to enter the cytoplasm and cause leakage of lactate dehydrogenase, thus acting in a membranolytic manner. Importantly, HMP-S7 exhibited anti-leukemic effect against patient-derived leukemic cells ex vivo. In conclusion, HMP-S7 is a selective anti-leukemic peptide with promise which requires further validation in preclinical and clinical studies.

TeaserIn silico screening of naturally occurring human milk peptides discovers a new anticancer peptide that kills leukemic cells in vitro and ex vivo. Lower limb in sprinters with larger relative mass but not larger normalized moment of inertia Inhomogeneous muscle hypertrophy in response to daily motor executions is a morphological adaptation in humans. Inhomogeneous morphological adaptation would change the mass distribution, which in turn may affect the mechanical difficulty in moving from an inertia perspective; however, the morphological adaptation from the inertia perspective has not been examined. Here we show no corresponding differences in the normalized mass and normalized moment of inertia between the sprinters and the untrained non-sprinters. We analyzed the fat- and water-separated magnetic resonance images from the lower limbs of 11 male sprinters (100 m best time of 10.44-10.83 s) and 12 untrained non-sprinters. The lower-limb relative mass was significantly larger in sprinters (18.7{+/-}0.7% body mass) than in non-sprinters (17.6{+/-}0.6% body mass), while the normalized moment of inertia of the lower limb around the hip in the anatomical position was similar between them (0.044{+/-}0.002 vs. 0.042{+/-}0.002 [a. u.]). The thigh relative mass in sprinters (12.9{+/-}0.4% body mass) was significantly larger than that in non-sprinters (11.9{+/-}0.4% body mass), whereas the shank and foot relative masses were similar. We revealed that the adaptation to sprinting in humans does not relatively increase the mechanical difficulty to swing the lower limb in terms of inertia, even though the lower-limb mass increases, reflecting muscular hypertrophy. This is suggested to be one of the significant advantages of human morphology for adaptability to explosive motor tasks.

NEW & NOTEWORTHYWe compared the lower-limb inertia properties between male sprinters and untrained non-sprinters by using the fat- and water-separated magnetic resonance images. Sprinters had lower limbs with a larger relative mass but not a larger normalized moment of inertia than non-sprinters. We suggest one of the practical advantages of human morphological characteristics for their adaptation to explosive motor tasks, which provides a novel perspective to the literature for understanding human morphological adaptability. Density dependent interactions during growth mask the effect of interactions during flowering in pollinator-sharing annual plants Density dependent interactions are fundamental to community ecology, but studies often reduce the complex nature of species interactions. In plant ecology, interactions during vegetative growth and flowering are often considered separately, though both can affect reproductive output. Here we use communities of annual flowering plants in the genus Clarkia to ask how interactions during growth and flowering contribute to density dependence in plant seed production, and if pollinator behaviors explain apparent patterns in plant interactions during flowering. We measure seed set (seed number per ovule) and total fecundity (whole-plant seed production) of Clarkia focal plants in experimental interaction plots with the effect of pollinators experimentally removed through supplemental pollination or retained. We also observe pollinator behaviors in the plots and experimental arrays to document pollinator preference, constancy and joint attraction. During flowering, pollinators significantly changed the density dependent effects of Clarkia interactions on seed set in 31% of species interactions, and these changes corresponded to pollinator behaviors. Total fecundity, however, did not depend on interactions between Clarkia; instead, earlier-flowering, non-Clarkia forbs limited total fecundity. Our study shows that interactions during vegetative growth can preclude the effect of pollinator- mediated interactions on fecundity by limiting potential reproductive output. Simultaneously studying different types of species interactions allows for understanding the contingency of ecological outcomes. The obstacles and potential clues of prime editing applications in tomato, a dicot plant Precision genome editing is highly desired for crop improvement. The recently emerged CRISPR/Cas technology offers great potential applications in precision plant genome engineering. A prime editing (PE) approach combining a reverse transcriptase (RT) with a Cas9 nickase and a "priming" extended guide RNA has shown a high frequency for precise genome modification in mammalian cells and several plant species. Nevertheless, the applications of the PE approach in dicot plants are still limited and inefficient. We designed and tested prime editors for precision editing of a synthetic sequence in a transient assay and for desirable alleles of 10 loci in tomato by stable transformation. Our data obtained by targeted deep sequencing also revealed only low PE efficiencies in both the tobacco and tomato systems. Further assessment of the activities of the PE components uncovered potential reasons for the inefficiency of the PE complexes. Modifying the pegRNA sequences by shortening or introducing mismatches to the primer binding sequences (PBS) in order to reduce their melting temperatures (Tm) did not enhance the PE efficiency at the SlBMP21, SlALC and SlALS1 loci. Our data show challenges of PE approach in tomato, indicating a further improvement of the PE system for the successful applications such as use of improved expression systems. Our work provides an important clue for the successful application of the PE approach in crop improvement. Quantifying the Morphology and Mechanisms of Cancer Progression in 3D in-vitro environments: Integrating Experiments and Multiscale Models Mathematical models of cancer growth have become increasingly more accurate both in the space and time domains. However, the limited amount of data typically available has resulted in a larger number of qualitative rather than quantitative studies. In the present study, we provide an integrated experimental-computational framework for the quantification of the morphological characteristics and the mechanistic modelling of cancer progression in 3D environments. The proposed framework allows for the calibration of multiscale, spatiotemporal models of cancer growth using state-of-the-art 3D cell culture data, and their validation based on the resulting experimental morphological patterns. Its implementation enabled us to pursue two goals; first, the quantitative description of the morphology of cancer progression in 3D cultures, and second, the relation of tumour morphology with underlying biophysical mechanisms that govern cancer growth and migration. We applied this framework to the study of the spatiotemporal progression of Triple Negative Breast Cancer cells cultured in Matrigel scaffolds, and validated the hypothesis of chemotactic migration using a multiscale Keller-Segel model. The results revealed transient, non-random spatial distributions of cancer cells that consist of clustered, and dispersion patterns. The proposed model was able to describe the general characteristics of the experimental observations and suggests that cancer cells exhibited chemotactic migration and accumulation, as well as random motion during the examined time period of development. To our knowledge, this is the first time that a multiscale model is used to quantify the relationship between the spatial patterns and the underlying mechanisms of cancer growth in 3D environments. 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. Main protease mutants of SARS-CoV-2 variants remain susceptible to nirmatrelvir (PF-07321332) The COVID-19 pandemic continues to be a public health threat. Multiple mutations in the spike protein of emerging variants of SARS-CoV-2 appear to impact on the effectiveness of available vaccines. Specific antiviral agents are keenly anticipated but their efficacy may also be compromised in emerging variants. One of the most attractive coronaviral drug targets is the main protease (Mpro). A promising Mpro inhibitor of clinical relevance is the peptidomimetic nirmatrelvir (PF-07321332). We expressed Mpro of six SARS-CoV-2 lineages (C.37 Lambda, B.1.1.318, B.1.2, B.1.351 Beta, B.1.1.529 Omicron, P.2 Zeta), each of which carries a strongly prevalent missense mutation (G15S, T21I, L89F, K90R, P132H, L205V). Enzyme kinetics showed that these Mpro variants are similarly catalytically competent as the wildtype. We show that nirmatrelvir has similar potency against the variants as against the wildtype. Our in vitro data suggest that the efficacy of the specific Mpro inhibitor nirmatrelvir is not compromised in current COVID-19 variants.

Graphical abstract

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org.highwire.dtl.DTLVardef@182cc6org.highwire.dtl.DTLVardef@1239d10org.highwire.dtl.DTLVardef@11ca6d9org.highwire.dtl.DTLVardef@df53b_HPS_FORMAT_FIGEXP  M_FIG C_FIG Enhancing Sampling of Water Rehydration on Ligand Binding: A Comparison of Techniques 1Water often plays a key role in protein structure, molecular recognition, and mediating protein-ligand interactions. Thus, free energy calculations must adequately sample water motions, which often proves challenging in typical MD simulation timescales. Thus, the accuracy of methods relying on MD simulations ends up limited by slow water sampling. Particularly, as a ligand is removed or modified, bulk water may not have time to fill or rearrange in the binding site. In this work, we focus on several molecular dynamics (MD) simulation-based methods attempting to help rehydrate buried water sites: BLUES, using nonequilibrium candidate Monte Carlo (NCMC); grand, using grand canonical Monte Carlo (GCMC); and normal MD. We assess the accuracy and efficiency of these methods in rehydrating target water sites. We selected a range of systems with varying numbers of waters in the binding site, as well as those where water occupancy is coupled to the identity or binding mode of the ligand. We analyzed rehydration of buried water sites in binding pockets using both clustering of trajectories and direct analysis of electron density maps. Our results suggest both BLUES and grand enhance water sampling relative to normal MD and grand is more robust than BLUES, but also that water sampling remains a major challenge for all of the methods tested. The lessons we learned for these methods and systems are discussed. Plant-environment microscopy tracks interactions of Bacillus subtilis with plant roots across the entire rhizosphere Our understanding of plant-microbe interactions in soil is limited by the difficulty of observing processes at the microscopic scale throughout plants large volume of influence. Here, we present the development of 3D live microscopy for resolving plant-microbe interactions across the environment of an entire seedling growing in a transparent soil in tailor-made mesocosms, maintaining physical conditions for the culture of both plants and microorganisms. A tailor made dual-illumination light-sheet system acquired scattering signals from the plant whilst fluorescence signals were captured from transparent soil particles and labelled microorganisms, allowing the generation of quantitative data on samples approximately 3600 mm3 in size with as good as 5 m resolution at a rate of up to one scan every 30 minutes. The system tracked the movement of Bacillus subtilis populations in the rhizosphere of lettuce plants in real time, revealing previously unseen patterns of activity. Motile bacteria favoured small pore spaces over the surface of soil particles, colonising the root in a pulsatile manner. Migrations appeared to be directed towards the root cap, the point "first contact", before subsequent colonisation of mature epidermis cells. Our findings show that microscopes dedicated to live environmental studies present an invaluable tool to understand plant-microbe interactions. 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. AutoGGN: A Gene Graph Network AutoML Tool for Multi-Omics Research Omics data identifies biological characteristics from genetic to phenotypic levels during the life span. Molecular interaction networks have a fundamental impact on life activities. Integrating omics data and molecular interaction networks will help researchers delve into comprehensive information underlying the data. Here, we proposed a new multimodal method called AutoGGN to aggregate multi-omics data and molecular interaction networks based on graph convolutional neural networks. We evaluated AutoGGN using two different tasks: cancer type classification and single-cell stage classification. On both tasks, AutoGGN showed better performance compared to other methods, the trend is relevant to the ability of utilizing much more information from biological data. The phenomenon indicated AutoGGN has the potential to incorporate valuable information from molecular interaction networks and multi-omics data effectively. Furthermore, in order to provide a better understanding of the mechanism of prediction results, we assessed the explanation using SHAP module and identified the key genes contributing to the prediction of classification, which will provide insights for the downstream design of biological experiments. RapidoPGS: A rapid polygenic score calculator for summary GWAS data without a test dataset MotivationPolygenic scores (PGS) aim to genetically predict complex traits at an individual level. PGS are typically trained on genome-wide association summary statistics and require an independent test dataset to tune parameters. More recent methods allow parameters to be tuned on the training data, removing the need for independent test data, but approaches are computationally intensive. Based on fine-mapping principles, we present RapidoPGS, a flexible and fast method to compute PGS requiring summary-level GWAS datasets only, with little computational requirements and no test data required for parameter tuning.

ResultsWe show that RapidoPGS performs slightly less well than two out of three other widely-used PGS methods (LDpred2, PRScs, and SBayesR) for case-control datasets, with median r2 difference: -0.0092, -0.0042, and 0.0064, respectively, but up to 17,000-fold faster with reduced computational requirements. RapidoPGS is implemented in R and can work with user-supplied summary statistics or download them from the GWAS catalog.

Availability and implementationOur method is available with a GPL license as an R package from GitHub. Analysis of science journalism reveals gender and regional disparities in coverage Science journalism is a critical way in which the public can remain informed and benefit from new scientific findings. Such journalism also shapes the publics view of the current state of scientific findings and legitimizes experts. Those covering science can only cite and quote a limited number of sources. Sources may be identified by the journalists research or by recommendations by other scientists. In both cases, biases may influence who is identified and ultimately included as an expert. To analyze possible biases in science journalism, we analyzed 22,001 non-research articles published by Nature. We chose to analyze Nature non-research articles since its research articles provide a natural comparator. Our analysis considered two possible sources of disparity: gender and name origin. To explore these sources of disparity, we extracted cited authors names as well as extracted names of quoted speakers. While citations and quotations within a piece do not reflect the entire information-gathering process, they can provide insight into the demographics of visible sources. We then used the extracted names to predict gender and name origin of the cited authors and speakers.

In order to appropriately quantify the level of difference, we must identify a suitable reference set for comparison. We chose first and last authors within primary research articles in Nature and a subset of Springer Nature articles in the same time period as our comparator. In our analysis, we found a skew towards male quotation in Nature science journalism-related articles. However, quotation is trending toward equal representation at a faster rate than first and last authorship in academic publishing. Interestingly, we found that the gender disparity in Nature quotes was column-dependent, with the "Career Features" column reaching gender parity. Our name origin analysis found a significant over-representation of names with predicted Celtic/English origin and under-representation of names with a predicted East Asian origin. This finding was observed both in extracted quotes and journal citations, but dampened in citations. Correlation between speed and turning naturally arises for sparsely sampled cell movements Mechanisms regulating cell movement are not fully understood. One feature of cell movement that determines how far cells displace from an initial position is persistence, the ability to perform movements in a direction similar to the previous movement direction. Persistence is thus determined by turning angles between two sequential displacements and be characterized by an average turning angle or persistence time. Recent studies found that a cells average speed and turning are negatively correlated, suggesting a fundamental cell-intrinsic program whereby cells with a lower turning ability (i.e., larger persistence time) are intrinsically faster (or faster cells turn less). By simulating correlated or persistent random walks (PRWs) using two different frameworks (one based on von Mises-Fisher (vMF) distribution and another based on Ornstein-Uhlenbeck (OU) process) we show that the negative correlation between speed and turning naturally arises when cell trajectories are sub-sampled, i.e., when the frequency of sampling is lower than frequency at which cells make movements. This effect is strongest when the sampling frequency is on the order of magnitude with the typical cell persistence time and when cells vary in persistence time. Both conditions are observed for datasets of T cell movements in vivo that we have analyzed. In simulations the correlation arises due to randomness of cell movements resulting in highly variable persistence times for individual cells that with sub-sampling leads to large variability of average cell speeds. Interestingly, previously suggested methodology of calculating displacement of cell cohorts with different speeds resulted in similar results whether or not there is a cell-intrinsic correlation between cell speed and persistence. For both vMF- and OU-based simulations of PRWs we could find parameter values (distribution of persistence times, speeds, and sampling frequency) that matched experimentally measured correlations between speed and turning for two datasets of T cell movement in vivo suggesting that such simple correlations are not fully informative on the intrinsic link between speed and persistence. Our results thus suggest that sub-sampling may contribute to (and perhaps fully explains) the observed correlation between speed and turning at least for some cell trajectory data and emphasize the role of sampling frequency in inference of critical cellular parameters of cell motility such as speeds.

Secondary AbstractMeasurement of cell movements often results in a negative correlation between average speed and average turning angle suggesting an existence of a universal, cell-intrinsic movement program. We show that such a negative correlation may arise if cells in the population differ in their ability for persistent movement when the movement data are sub-sampled. We show that sub-sampling of cell trajectories generated using two different frameworks of persistent random walk can match the experimentally observed correlation between speed and turning for T cell movements in vivo. Nelfinavir markedly improves lung pathology in SARS-CoV-2-infected Syrian hamsters despite lack of an antiviral effect In response to the ongoing COVID-19 pandemic, repurposing of drugs for the treatment of SARS-CoV-2 infections is being explored. The HIV protease inhibitor Nelfinavir, widely prescribed in combination with other HIV inhibitors, has been shown to inhibit in vitro SARS-CoV-2 replication. We here report on the effect of Nelfinavir in the Syrian hamster SARS-CoV-2 infection model. Although treatment of infected hamsters with either 15 or 50 mg/kg BID Nelfinavir [for four consecutive days, initiated on the day of infection] does not reduce viral RNA loads nor infectious virus titres in the lungs compared to the vehicle control, the drug reduced virus-induced lung pathology to nearly the baseline scores of healthy animals. A substantial interstitial infiltration of neutrophils is observed in the lungs of treated (both infected and uninfected) animals. The protective effect of Nelfinavir on SARS-CoV-2-induced lung pathology (at doses that are well tolerated and that result in exposures nearing those observed in HIV-infected patients) may lay the foundation for clinical studies with this widely used drug. Genome archaeology of two laboratory Salmonella enterica enterica sv Typhimurium The Salmonella research community has used strains and bacteriophages over decades, exchanging useful new isolates among laboratories for study of cell surface antigens, metabolic pathways and restriction-modification studies. Here we present the sequences of two laboratory Salmonella strains (STK005, an isolate of LB5000; and its descendant ER3625). In the ancestry of LB5000, segments of ~15 and ~42 kb were introduced from Salmonella enterica sv Abony 103 into Salmonella enterica sv Typhimurium LT2, forming strain SD14; this strain is thus a hybrid of S. enterica isolates. Strains in the SD14 lineage were used to define flagellar antigens from the 1950s to the 1970s, and to define three restriction-modification systems from the 1960s to the 1980s. LB5000 was also used as host in phage typing systems used by epidemiologists. In the age of cheaper and easier sequencing, this resource will provide access to the sequence that underlies the extensive literature. Ineffectual AEC1 differentiation from KRT8hi transitional state without fibrosis is associated with fatal COVID-19 ARDS ARDS due to COVID-19 and other etiologies results from injury to the alveolar epithelial cell (AEC) barrier resulting in noncardiogenic pulmonary edema, which causes acute respiratory failure; clinical recovery requires epithelial regeneration. During physiologic regeneration in mice, AEC2s proliferate, exit the cell cycle, and transiently assume a transitional state before differentiating into AEC1s; persistence of the transitional state is associated with pulmonary fibrosis in humans. It is unknown whether transitional cells emerge and differentiate into AEC1s without fibrosis in human ARDS and why transitional cells differentiate into AEC1s during physiologic regeneration but persist in fibrosis. We hypothesized that incomplete but ongoing AEC1 differentiation from transitional cells without fibrosis may underlie persistent barrier permeability and fatal acute respiratory failure in ARDS. Immunostaining of postmortem ARDS lungs revealed abundant transitional cells in organized monolayers on alveolar septa without fibrosis. They were typically cuboidal or partially spread, sometimes flat, and occasionally expressed AEC1 markers. Immunostaining and/or interrogation of scRNAseq datasets revealed that transitional cells in mouse models of physiologic regeneration, ARDS, and fibrosis express markers of cell cycle exit but only in fibrosis express a specific senescence marker. Thus, in severe, fatal early ARDS, AEC1 differentiation from transitional cells is incomplete, underlying persistent barrier permeability and respiratory failure, but ongoing without fibrosis; senescence of transitional cells may be associated with pulmonary fibrosis. Deep learning: step forward to high-resolution in vivo shortwave infrared imaging Shortwave infrared window (SWIR: 1000-1700 nm) represents a major improvement compared to the NIR-I region (700-900 nm) in terms of temporal and spatial resolutions in depths down to 4 mm. SWIR is a fast and cheap alternative to more precise methods such as X-ray and opto-acoustic imaging. Main obstacles in SWIR imaging are the noise and scattering from tissues and skin that reduce the precision of the method. We demonstrate that the combination of SWIR in vivo imaging in the NIRIIb region (1500-1700 nm) with advanced deep learning image analysis allows to overcome these obstacles and making a large step forward to high resolution imaging: it allows to precisely segment vessels from tissues and noise, provides morphological structure of the vessels network, with learned pseudo-3D shape, their relative position, dynamic information of blood vascularization in depth in small animals and distinguish the vessels types: artieries and veins. For demonstration we use neural network IterNet that exploits structural redundancy of the blood vessels, which provides a useful analysis tool for raw SWIR images. Differential metabolism of arsenicals regulates Fps1-mediated arsenite transport Arsenic is an environmental toxin that exists mainly as pentavalent arsenate and trivalent arsenite. Both forms activate the yeast SAPK Hog1, but with different consequences. We describe a mechanism by which cells distinguish between these arsenicals through one-step metabolism to differentially regulate the bidirectional glycerol channel Fps1, an adventitious port for arsenite. Cells exposed to arsenate reduce it to thiol-reactive arsenite, which modifies a set of cysteine residues in target proteins; whereas cells exposed to arsenite metabolize it to methylarsenite, which modifies an additional set of cysteine residues. Hog1 becomes arsenylated, which prevents it from closing Fps1. However, this block is overcome in cells exposed to arsenite through methylarsenylation of Acr3, an arsenite efflux pump that we found also regulates Fps1 directly. This adaptation allows cells to restrict arsenite entry through Fps1, but also allows its exit when produced from arsenate exposure. These results have broad implications for understanding how SAPKs activated by diverse stressors can drive stress-specific outputs.

Summary (for JCB table of contents)

Jongmin Lee, David E. Levin

Lee and Levin investigate the question of how different stressors can drive divergent outputs from an active SAPK. The work describes the mechanism by which two forms of arsenic that both activate the yeast SAPK Hog1 differentially regulate the glycerol channel Fps1. HYBRID REACTION-DIFFUSION AND CLOCK-AND-WAVEFRONT MODEL FOR THE ARREST OF OSCILLATIONS IN THE SOMITOGENESIS SEGMENTATION CLOCK AO_SCPLOWBSTRACTC_SCPLOWThe clock and wavefront paradigm is arguably the most widely accepted model for explaining the embryonic process of somitogenesis. According to this model, somitogenesis is based upon the interaction between a genetic oscillator, known as segmentation clock, and a differentiation wavefront, which provides the positional information indicating where each pair of somites is formed. Shortly after the clock and wavefront paradigm was introduced, Meinhardt presented a conceptually different mathematical model for morphogenesis in general, and somitogenesis in particular. Recently, Cotterell et al. rediscovered an equivalent model by systematically enumerating and studying small networks performing segmentation. Cotterell et al. called it a progressive oscillatory reaction-diffusion (PORD) model. In the Meinhardt-PORD model, somitogenesis is driven by short-range interactions and the posterior movement of the front is a local, emergent phenomenon, which is not controlled by global positional information. With this model, it is possible to explain some experimental observations that are incompatible with the clock and wavefront model. However the Meinhardt-PORD model has some important disadvantages of its own. Namely, it is quite sensitive to fluctuations and depends on very specific initial conditions (which are not biologically realistic). In this work, we propose an equivalent Meinhardt-PORD model, and then amend it to couple it with a wavefront consisting of a receding morphogen gradient. By doing so, we get a hybrid model between the Meinhardt-PORD and the clock-and-wavefront ones, which overcomes most of the deficiencies of the two originating models.

Somitogenesis, the process by which somites are formed, is an essential developmental stage in many vertebrates. This process occurs with a strikingly regular periodicity, that is preserved among embryos of a single species. The clock and wavefront paradigm is arguably the most widely accepted model for explaining somitogenesis. However, it is incapable of explaining some experimental facts, like the appearance of somites in the absence of an external wavefront (i.e. a receding morphogen gradient). Shortly after the clock and wavefront paradigm was introduced, Meinhardt presented a conceptually different mathematical model for morphogenesis in general, and somitogenesis in particular. Recently, Cotterell et al. rediscovered an equivalent model by systematically enumerating and studying small networks performing segmentation, and called it a progressive oscillatory reaction-diffusion (PORD) model. The Meinhardt-PORD model tackles some of the deficiencies of the clock and wave-front models, but it has some serious issues of its own. In the present work, we introduce an equivalent Meinhardt-PORD model, and then amend it to couple it with a receding morphogen gradient. By doing so, we get a hybrid model that incorporates characteristics of the Meinhardt-PORD and clock-and-wavefront models. We show that this hybrid model under-goes a bifurcation, from a stable to an unstable limit cycle, as the value of the parameter accounting for a background regulatory input (associated to the receding morphogen gradient) decreases. This bifurcation allows the model to explain why somites can form in the absence of an external wavefront, reassesses the role of the receding morphogen gradient as a conductor for somitogenesis, and makes the model behavior robust to random fluctuations, as well as independent from specific initial conditions (the latter, are two of the weak points of the Meinhardt-PORD model). We argue that this findings provide convincing evidence that reaction-diffusion and positional information (receding morphogen gradient) mechanisms could work together in somitogenesis. Long term analysis of social structure: evidence of age-based consistent associations in male Alpine ibex Despite its recognized importance for understanding the evolution of animal sociality as well as for conservation, long term analysis of social networks of animal populations is still relatively uncommon. We investigated social network dynamics in males of a gregarious mountain ungulate (Alpine ibex, Capra ibex) over ten years focusing on groups, sub-groups and individuals, exploring the dynamics of sociality over different scales. Despite the social structure changing between seasons, the Alpine ibex population was highly cohesive: fission-fusion dynamics lead almost every male in the population to associate with each other male at least once. Nevertheless, we found that male Alpine ibex showed preferential associations that were maintained across seasons and years. Age seemed to be the most important factor driving preferential associations while other characteristics, such as social status, appeared less crucial. We also found that centrality measures were influenced by age and were also related to individual physical condition. The multi-scale and long-term frame of our study helped us show that ecological constrains, such as resource availability, may play a role in shaping associations in a gregarious species, but they cannot solely explain sociality and preferential association that are likely also to be driven by life-history linked physiological and social needs. Our results highlight the importance of long-term studies based on individually recognizable subjects to help us build on our understanding of the evolution of animal sociality.