White matter myelination during early infancy is explained by spatial gradients and myelin content at birth Development of myelin, a fatty sheath that insulates nerve fibers, is critical for brain function. Myelination during infancy has been studied with histology, but postmortem data cannot evaluate the longitudinal trajectory of white matter development. Here, we obtained longitudinal diffusion MRI and quantitative MRI measures of R1 in 0, 3 and 6 months-old human infants, and (ii) developed an automated method to identify white matter bundles and quantify their properties in each infants brain. We find that R1 increases from newborns to 6-months-olds in all bundles. R1 development is nonuniform: there is faster development in white matter that is less mature in newborns, and along inferior-to-superior as well as anterior-to-posterior spatial gradients. As R1 is linearly related to myelin fraction in white matter bundles, these findings open new avenues to elucidate typical and atypical white matter myelination in early infancy, which has important implications for early identification of neurodevelopmental disorders.
Connectome-based predictions reveal developmental change in the functional architecture of sustained attention and working memory Sustained attention (SA) and working memory (WM) are critical processes, but the brain networks supporting these abilities in development are unknown. We characterized the functional brain architecture of SA and WM in 9-11-year-old children and adults. First, we found that adult network predictors of SA generalized to predict individual differences and fluctuations in SA in youth. A WM network model predicted WM performance both across and within children--and captured individual differences in later recognition memory--but underperformed in youth relative to adults. We next characterized functional connections differentially related to SA and WM in youth compared to adults. Results revealed two network configurations: a dominant architecture predicting performance in both age groups and a secondary architecture, more prominent for WM than SA, predicting performance in one. Thus, functional connectivity predicts SA and WM in youth, with networks predicting WM changing more from preadolescence to adulthood than those predicting SA.
Integrative Modelling of Signalling Network Dynamics Identifies Cell Type-selective Therapeutic Strategies for FGFR4-driven Cancers Oncogenic FGFR4 signalling represents a potential therapeutic target in many cancer types, including triple negative breast cancer (TNBC) and hepatocellular carcinoma (HCC). However, resistance to single-agent therapy directed at FGFR4 remains a major challenge, prompting the need to identify more effective combinatorial therapeutic strategies. Here, we integrated computational network modelling and experimental validation to characterise dynamic reprogramming of the FGFR4 signalling network in TNBC following FGFR4 kinase inhibition. We found that AKT, which signals downstream of FGFR4, displayed a rapid and potent reactivation following FGFR4 targeting. Through model-based simulation and systematic prediction of the effect of co-targeting specific network nodes, we predicted, and validated experimentally, strong synergism of co-targeting FGFR4 and particular ErbB kinases or AKT, but not the upstream kinase PI3K. Further, incorporation of protein expression data from hundreds of cancer cell types enabled us to adapt our model to other diverse cellular contexts, leading to the prediction that while AKT rebound occurs frequently, it is not a general phenomenon. Instead, ERK is reactivated in a subset of cell types, including the FGFR4-driven HCC cell line Hep3B. This was subsequently corroborated, and moreover, co-targeting FGFR4 and MEK in Hep3B cells markedly enhanced inhibition of cell proliferation. Overall, these findings provide novel insights into the dynamics of drug-induced network remodelling in cancer cells, highlight the impact of protein expression heterogeneity on network response to targeted therapy and identify candidate cell type-selective combination treatments for FGFR4-driven cancer. LY-CoV1404 (bebtelovimab) potently neutralizes SARS-CoV-2 variants SARS-CoV-2 neutralizing monoclonal antibodies (mAbs) can reduce the risk of hospitalization when administered early during COVID-19 disease. However, the emergence of variants of concern has negatively impacted the therapeutic use of some authorized mAbs. Using a high throughput B-cell screening pipeline, we isolated a highly potent SARS-CoV-2 spike glycoprotein receptor binding domain (RBD)-specific antibody called LY-CoV1404 (also known as bebtelovimab). LY-CoV1404 potently neutralizes authentic SARS-CoV-2 virus, including the prototype, B.1.1.7, B.1.351 and B.1.617.2). In pseudovirus neutralization studies, LY-CoV1404 retains potent neutralizing activity against numerous variants including B.1.1.7, B.1.351, B.1.617.2, B.1.427/B.1.429, P.1, B.1.526, B.1.1.529, and the BA.2 subvariant and retains binding to spike proteins with a variety of underlying RBD mutations including K417N, L452R, E484K, and N501Y. Structural analysis reveals that the contact residues of the LY-CoV1404 epitope are highly conserved with the exception of N439 and N501. Notably, the binding and neutralizing activity of LY-CoV1404 is unaffected by the most common mutations at these positions (N439K and N501Y). The breadth of reactivity to amino acid substitutions present among current VOC together with broad and potent neutralizing activity and the relatively conserved epitope suggest that LY-CoV1404 has the potential to be an effective therapeutic agent to treat all known variants causing COVID-19.

In BriefLY-CoV1404 is a potent SARS-CoV-2-binding antibody that neutralizes all known variants of concern and whose epitope is rarely mutated.

HighlightsO_LILY-CoV1404 potently neutralizes SARS-CoV-2 authentic virus and known variants of concern including the B.1.1.529 (Omicron), the BA.2 Omicron subvariant, and B.1.617.2 (Delta) variants
C_LIO_LINo loss of potency against currently circulating variants
C_LIO_LIBinding epitope on RBD of SARS-CoV-2 is rarely mutated in GISAID database
C_LIO_LIBreadth of neutralizing activity and potency supports clinical development
C_LI GFAP splice variants fine-tune glioma cell invasion and tumour dynamics by modulating migration persistence Glioma is the most common form of malignant primary brain tumours in adults. Their highly invasive nature makes the disease incurable to date, emphasizing the importance of better understanding the mechanisms driving glioma invasion. Glial fibrillary acidic protein (GFAP) is an intermediate filament protein that is characteristic for astrocyte- and neural stem cell-derived gliomas. Glioma malignancy is associated with changes in GFAP alternative splicing, as the canonical isoform GFAP is downregulated in higher-grade tumours, leading to increased dominance of the GFAP{delta} isoform in the network. In this study, we used intravital imaging and an ex vivo brain slice invasion model. We show that the GFAP{delta} and GFAP isoforms differentially regulate the tumour dynamics of glioma cells. Depletion of either isoform increases the migratory capacity of glioma cells. Remarkably, GFAP{delta}-depleted cells migrate randomly through the brain tissue, whereas GFAP-depleted cells show a directionally persistent invasion into the brain parenchyma. This study shows that distinct compositions of the GFAP-network lead to specific migratory dynamics and behaviours of gliomas. 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. Interplay between receptor binding, immune escape and protein stability determines the natural selection of SARS-CoV-2 variants Emergence of new SARS-CoV-2 variants has raised concerns at the effectiveness of vaccines and antibody therapeutics developed against the unmutated wild-type virus. We examined the effect of 12 most commonly occurring mutations in the receptor binding domain on its expression, stability, activity, and antibody escape potential-some of the factors that may influence the natural selection of mutants. Recombinant proteins were expressed in human cells. Stability was measured using thermal denaturation melts. Activity and antibody escape potential were measured using isothermal titration calorimetry in terms of binding to ACE2 and to a neutralizing human antibody CC12.1, respectively. Our results show that variants differ in their expression levels with the two least stable variants showing lesser expression. Out of the 8 well-expressed mutants, only 2 (N501Y and K417T/E484K/N501Y) showed stronger affinity to ACE2, 4 (Y453F, S477N, T478I and S494P) have similar affinity, whereas the other 2 (K417N and E484K) have weaker affinity when compared to the wild-type. In terms of CC12.1 binding, when compared to the wild-type, 4 variants (K417N, Y453F, N501Y and K417T/E484K/N501Y) have weaker affinity, 2 (S477N and S494P) have similar affinity, and 2 (T478I and E484K) have stronger affinity. Taken together, these results indicate that multiple factors contribute towards the natural selection of variants, and all these factors need be considered to understand the evolution of the virus. In addition, since not all variants can escape a given neutralizing antibody, antibodies to treat new variants can be chosen based on the specific mutations in that variant. A Comparative Analysis of Novel Deep Learning and Ensemble Learning Models to Predict the Allergenicity of Food Proteins Traditional food allergen identification mainly relies on in vivo and in vitro experiments, which often needs a long period and high cost. The artificial intelligence (AI)-driven rapid food allergen identification method has solved the above mentioned two drawbacks and is becoming an efficient auxiliary tool. Aiming to overcome the limitations of lower accuracy of traditional machine learning models in predicting the allergenicity of food proteins, this work proposed to introduce deep learning model - transformer with self-attention mechanism, ensemble learning models (representative as Light Gradient Boosting Machine (LightGBM) eXtreme Gradient Boosting (XGBoost)) to solve the problem. In order to highlight the superiority of the proposed novel method, the study also selected various commonly used machine learning models as the baseline classifiers. The results of 5-fold cross-validation showed that the AUC of the deep model was the highest (0.9578), which was better than the ensemble learning and baseline algorithms. But the deep model need to be pre-trained, and the training cost is the highest. By comparing the characteristics of the transformer model and boosting models, it can be analyzed that, each model has its own advantage, which provides novel clues and inspiration for the rapid prediction of food allergens in the future. First detection of herpesvirus and frequency of mycoplasma infection in free-ranging Hermann s tortoises (Testudo hermanni), and in potential pet vectors AO_SCPLOWBSTRACTC_SCPLOWTwo types of pathogens cause highly contagious upper respiratory tract diseases (URTD) in Chelonians: testudinid herpesviruses (TeHV) and a mycoplasma (Mycoplasma agassizii). In captivity, these infections are frequent and can provoke outbreaks. Pet trade generates international flow of tortoises, often without sanitary checking; individuals intentionally or accidentally released in the wild may spread pathogens. A better understanding of the transmission of infectious agents from captivity to wild tortoises is needed. Many exotic individuals have been introduced in populations of the endangered western Hermanns tortoise (Testudo hermanni hermanni), notably spur-thighed tortoises (Testudo graeca). We assessed the presence of TeHV and mycoplasma in native western Hermanns tortoises and in potential pet vectors in south-eastern France. Using a large sample (N=572 tortoises), this study revealed, by PCR, the worrying presence of herpesvirus in 7 free-ranging individuals (3 sub-populations). Additionally, Mycoplasma agassizii was detected, by PCR, in 15 of the 18 populations sampled with a frequency ranging from 3.4% (1 of 29 tortoises) to 25% (3 of 12 tortoises). Exotic spur-thighed tortoises showed high frequency of mycoplasma infection in captivity (18.2%) and in individuals (50%) found in native Hermanns tortoise sub-populations, suggesting that this species could be a significant vector. The paucity of information of TeHV on European tortoise URTD in natural settings, especially in combination with mycoplasma, prompts for further studies. Indeed, sick tortoises remain concealed and may not be easily detected in the field. Our results indicate a good health for most infected tortoise but it should be screened in the field as well as in captivity. 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. Universal protein misfolding intermediates can bypass the proteostasis network and remain soluble and less-functional Misfolded protein conformations with decreased functionality can bypass the proteostasis machinery and remain soluble in vivo. This is an unexpected phenomenon as several cellular quality control mechanisms have evolved to rid cells of misfolded proteins. Three questions, then, are: how is it structurally possible for long-lived, soluble, misfolded proteins to bypass the proteostasis machinery and processes? How widespread are these soluble, misfolded states across the proteome? And how long do they persist for? Here, we address these questions using coarse-grain molecular dynamics simulations of the synthesis, termination, and post-translational dynamics of a representative set of cytosolic E. coli proteins. We predict that half of all proteins exhibit subpopulations of misfolded conformations that are likely to bypass molecular chaperones, avoid aggregation, and not be rapidly degraded. These misfolded states may persist for months or longer for some proteins. Structurally characterizing these misfolded states, we observe they have a large amount of native structure, but also contain localized misfolded regions from non-native changes in entanglement, in which a protein segment threads through a loop formed by another portion of the protein that is not found in the native state. The surface properties of these misfolded states are native like, suggesting they may bypass the proteostasis machinery and its regulatory processes to remain soluble, while their entanglements make these states long-lived kinetic traps, as disentanglement requires unfolding of already folded portions of the protein. In terms of function, we predict that one-third of proteins have subpopulations that misfold into less-functional states that have structurally perturbed functional sites yet remain soluble. Data from limited-proteolysis mass spectrometry experiments, which interrogate the misfolded conformations populated by proteins upon unfolding and refolding, are consistent with the structural changes seen in the entangled states of glycerol-3-phosphate dehydrogenase upon misfolding. These results provide an explanation for how proteins can misfold into soluble conformations with reduced functionality that can bypass cellular quality controls, and indicate, unexpectedly, this may be a wide-spread phenomenon in proteomes. Such entanglements are observed in many native structures, suggesting the non-native entanglements we observe are plausible. More broadly, these near-native entangled structures suggest a hypothesis for how synonymous mutations can modulate downstream protein structure and function, with these mutations partitioning nascent proteins between these kinetically trapped states. Data-Driven Network Models for Genetic Circuits From Time-Series Data with Incomplete Measurements Synthetic gene networks are frequently conceptualized and visualized as static graphs. This view of biological programming stands in stark contrast to the transient nature of biomolecular interaction, which is frequently enacted by labile molecules that are often unmeasured. Thus, the network topology and dynamics of synthetic gene networks can be difficult to verify in vivo or in vitro, due to the presence of unmeasured biological states. Here we introduce the dynamical structure function as a new mesoscopic, data-driven class of models to describe gene networks with incomplete measurements. We introduce a network reconstruction algorithm and a code base for reconstructing the dynamical structure function from data, to enable discovery and visualization of graphical relationships in a genetic circuit diagram as time-dependent functions rather than static, unknown weights. We prove a theorem, showing that dynamical structure functions can provide a data-driven estimate of the size of crosstalk fluctuations from an idealized model. We illustrate this idea with numerical examples. Finally, we show how data-driven estimation of dynamical structure functions can explain failure modes in two experimentally implemented genetic circuits, a historical genetic circuit and a new E. coli based transcriptional event detector. TSC22D4 interacts with Akt1 in response to metabolic and stress signals Transforming Growth Factor {beta} 1 Stimulated Clone 22 D4 (TSC22D4) is an intrinsically disordered protein that regulates cellular and physiological processes such as cell proliferation, cellular senescence as well as hepatic glucose and lipid metabolism. The molecular mechanism of TSC22D4 action in these cellular and metabolic functions, however, remains largely elusive. Here, we identified TSC22D4 as a novel protein kinase B/Akt1 interacting protein, a critical mediator of insulin/PI3K signaling pathway implicated in diverse set of diseases including type 2 diabetes, obesity and cancer. TSC22D4 interacts with Akt1 not constitutively but rather in a regulatory manner. While glucose and insulin stimulation of cells or refeeding of mice impair the hepatic TSC22D4-Akt1 interaction, inhibition of mitochondria and oxidative stress, promote it; indicating that extra- and intra-cellular cues play a key role in controlling TSC22D4-Akt1 interaction. Our results also demonstrate that together with its dimerization domain, i.e. the TSC box, TSC22D4 requires its intrinsically disordered region (D2 domain) to interact with Akt1. To understand regulation of TSC22D4 function further, we employed tandem mass spectrometry and identified 15 novel phosphorylation sites on TSC22D4. Similar to TSC22D4-Akt1 interaction, TSC22D4 phosphorylation also responds to environmental signals such as starvation, mitochondrial inhibition and oxidative stress. Interestingly, 6 out of the 15 novel phosphorylation sites lie within the TSC22D4 D2 domain, which is required for TSC22D4-Akt1 interaction. Characterization of the regulation and function of these novel phosphorylation sites, in the future, will shed light on our understanding of the role of TSC22D4-Akt1 interaction in both cell biological and physiological functions. Overall, our findings postulate a model whereby TSC22D4 acts as an environmental sensor and interacts with Akt1 to regulate cell proliferation, cellular senescence as well as maintain metabolic homeostasis. OrganoID: a versatile deep learning platform for tracking and analysis of single-organoid dynamics Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug screening. Dynamic changes in individual organoid morphology, number, and size can indicate important drug responses, however these metrics are difficult and labor-intensive to obtain for high-throughput image datasets. Here, we present OrganoID, a robust image analysis platform that automatically recognizes, labels, and tracks single organoids, pixel-by-pixel, in brightfield and phase-contrast microscopy experiments. The platform was trained on images of pancreatic cancer organoids and validated on separate images of pancreatic, lung, colon, and adenoid cystic carcinoma organoids, which showed excellent agreement with manual measurements of organoid count (96%) and size (95%) without any parameter adjustments. Single-organoid tracking accuracy remained above 89% over a four-day time-lapse microscopy study. Automated single-organoid morphology analysis of a chemotherapy dose-response experiment identified decreased organoid circularity as an important morphological feature reflecting drug response. OrganoID enables straightforward, detailed, and accurate image analysis to accelerate the use of organoids in high-throughput, data-intensive biomedical applications. 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. A mixture of innate cryoprotectants is key for freeze tolerance and cryopreservation of a drosophilid fly larva. Insects that naturally tolerate internal freezing produce complex mixtures of multiple cryoprotectants (CPs). Better knowledge on composition of these mixtures, and on mechanisms of how the individual CPs interact, could inspire development of laboratory CP formulations optimized for cryopreservation of cells and other biological material. Here we identify and quantify (using high resolution mass spectrometry) a range of putative CPs in larval tissues of a subarctic fly, Chymomyza costata that survives long-term cryopreservation in liquid nitrogen. The CPs (proline, trehalose, glutamine, asparagine, glycine betaine, glycerophosphoethanolamine, glycerophosphocholine, and sarcosine) accumulate in hemolymph in a ratio of 313:108:55:26:6:4:3:0.5 mmol.L-1. Using calorimetry, we show that the artificial mixtures, mimicking the concentrations of major CPs in hemolymph of freeze-tolerant larvae, suppress the melting point of water and significantly reduce the ice fraction. We demonstrate in a bioassay that mixtures of CPs administered through the diet act synergistically rather than additively to enable cryopreservation of otherwise freeze-sensitive larvae. Using MALDI-MSI, we show that during slow extracellular freezing trehalose becomes concentrated in partially dehydrated hemolymph where it stimulates transition to the amorphous glass phase. In contrast, proline moves to the boundary between extracellular ice and dehydrated hemolymph and tissues where it likely forms a layer of dense viscoelastic liquid. We propose that amorphous glass and viscoelastic liquids may protect macromolecules and cells from thermomechanical shocks associated with freezing and transfer into and out of liquid nitrogen.

Summary statementThe composition of natural cryoprotectant mixture of the extremely freeze-tolerant insect is revealed. Components of the mixture work in synergy and behave differently during organismal freezing and cryopreservation. Bacterial and fungal communities experience rapid secondary succession during the first year following a wildfire in a California chaparral. The rise in wildfire frequency and severity across the globe has increased interest in secondary succession. However, despite the role of soil microbial communities in the regeneration of post-fire vegetation and biogeochemical cycling, the lack of measurements immediately post-fire and at high temporal resolution has resulted in a limited understanding of microbial secondary succession. To fill this knowledge gap, we sampled soils at 17, 25, 34, 67, 95, 131, 187, 286, and 376 days after a Southern California wildfire in fire-adapted chaparral shrublands. We assessed bacterial and fungal biomass with qPCR of 16S and 18S and richness and composition with Illumina MiSeq sequencing of 16S and ITS2 amplicons. Fire severely reduced bacterial biomass by 47% and richness by 46%, but the impacts were stronger for fungi, with biomass decreasing by 86% and richness by 68%. While bacterial biomass and richness oscillated in response to precipitation, the declines in biomass and richness for both groups persisted for the entire year. In contrast to the unburned plots, burned fungal and bacterial communities experienced rapid succession, with 5-6 compositional turnover periods. Analogous to plants, "fire-loving" pyrophilous microbes increased post-fire and drove successional dynamics. Interestingly, many of the same pyrophilous taxa found in forests worldwide also dominated post-fire chaparral and traded off markedly in abundance over time. For fungi, an initial peak in the Basidiomycete yeast Geminibasidium traded off with the filamentous Ascomycetes Pyronema, Aspergillus, and Penicillium. For bacteria, the Proteobacteria genus Massilia dominated burned plots throughout the year, but the following most dominant bacteria, the Firmicute Bacillus and Proteobacteria Noviherbaspirillum, traded off in abundance over time. Our unprecedented high-resolution temporal sampling allowed us to capture post-fire microbial secondary successional dynamics and show that putative tradeoffs in thermotolerance, colonization, and competition among dominant pyrophilous microbes control microbial succession with possible implications for ecosystem function. The contributions from the progenitor genomes of the mesopolyploid Brassiceae are evolutionarily distinct but functionally compatible The members of the tribe Brassiceae share a whole genome triplication (WGT), and one proposed model for its formation is a "two-step" pair of hybridizations producing hexaploid descendants. However, evidence for this model is incomplete, and the evolutionary and functional constraints that drove evolution after the hexaploidy are even less understood. Here we report a new genome sequence of Crambe hispanica, a species sister to most sequenced Brassiceae. Using this new genome and three others that share the hexaploidy, we traced the history of gene loss after the WGT using POInT (the Polyploidy Orthology Inference Tool). We confirm the two-step formation model and infer that there was a significant temporal gap between those two allopolyploidizations, with about a third of the gene losses from the first two subgenomes occurring prior to the arrival of the third. We also, for the 90,000 individual genes in our study, make parental "subgenome" assignments, inferring, with measured uncertainty, which of the progenitor genomes of the allohexaploidy each gene derives from. We further show that each subgenome has a statistically distinguishable rate of homoeolog losses. There is little indication of functional distinction between the three subgenomes: the individual subgenomes show no patterns of functional enrichment, no excess of shared protein-protein or metabolic interactions between their members, and no biases in their likelihood of having experienced a recent selective sweep. We propose a "mix and match" model of allopolyploidy, where subgenome origin drives homoeolog loss propensities but where genes from different subgenomes function together without difficulty. Fatal COVID-19 and non-COVID-19 Acute Respiratory Distress Syndrome is Associated with Incomplete Alveolar Type 1 Epithelial Cell Differentiation from the Transitional State Without Fibrosis 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. Constraints on the evolution of toxin-resistant Na,K-ATPases have limited dependence on sequence divergence A growing body of theoretical and experimental evidence suggests that intramolecular epistasis is a major determinant of rates and patterns of protein evolution and imposes a substantial constraint on the evolution of novel protein functions. Here, we examine the role of intramolecular epistasis in the recurrent evolution of resistance to cardiotonic steroids (CTS) across tetrapods, which occurs via specific amino acid substitutions to the -subunit family of Na,K-ATPases (ATP1A). After identifying a series of recurrent substitutions at two key sites of ATP1A that are predicted to confer CTS resistance in diverse tetrapods, we then performed protein engineering experiments to test the functional consequences of introducing these substitutions onto divergent species backgrounds. In line with previous results, we find that substitutions at these sites can have substantial background-dependent effects on CTS resistance. Globally, however, these substitutions also have pleiotropic effects that are consistent with additive rather than background-dependent effects. Moreover, the magnitude of a substitutions effect on activity does not depend on the overall extent of ATP1A sequence divergence between species. Our results suggest that epistatic constraints on the evolution of CTS-resistant forms of Na,K-ATPase likely depend on a small number of sites, with little dependence on overall levels of protein divergence. We propose that dependence on a limited number sites may account for the observation of convergent CTS resistance substitutions observed among taxa with highly divergent Na,K-ATPases.

Significance StatementIndividual amino acid residues within a protein work in concert to produce a functionally coherent structure that must be maintained even as orthologous proteins in different species diverge over time. Given this dependence, we expect identical mutations to have more similar effects on protein function in more closely related species. We tested this hypothesis by performing protein-engineering experiments on ATP1A, an enzyme mediating target-site insensitivity to cardiotonic steroids (CTS) in diverse animals. These experiments reveal that the phenotypic effects of substitutions can sometimes be background-dependent, but also that the magnitude of these phenotypic effects does not correlate with overall levels of ATP1A sequence divergence. Our results suggest that epistatic constraints are determined by states at a small number of sites, potentially explaining the frequent convergent CTS resistance substitutions among Na,K-ATPases of highly divergent taxa. A cell type-specific multiomics uncovers a guard cell-specific RAF15-SnRK2.6/OST1 kinase cascade Multicellular organisms such as plants contain different cell types with specialized functions. Analyzing the characteristics of each cell type reveals specific cell functions and enhances understanding of organization and function at the organismal level. Here we report a highly-sensitive and efficient cell type-specific multiomics pipeline, combining simplified flow cytometry-based cell sorting for fluorescent protoplasts and optimized nanoscale proteomics and metabolomics methods, which allow in-depth analysis of the proteomes and metabolomes of a particular cell type. Using this method, we quantitatively compared the proteomes and metabolomes of guard cells and mesophyll cells and revealed that the enrichment of signal transduction-related proteins enables guard cells to respond rapidly to various environmental stimuli. We uncovered a guard cell-specific kinase cascade whereby RAF15 and OST1 mediate ABA-induced stomatal closure. This pipeline can be applied to various cell types in plant or non-plant systems to learn how cells function in highly organized multicellular organisms. In vivo profiling of site-specific human cancer cell states in zebrafish Tissue microenvironments affect the functional states of cancer cells, but determining these influences in vivo has remained a significant challenge. We present a quantitative high-resolution imaging assay of cancer cell morphology in zebrafish xenografts to probe functional adaptation to variable cell extrinsic cues and molecular interventions. We focus on Ewing Sarcoma, a pediatric cancer driven by a single oncogenic fusion protein EWSR1-FLI1, and with little to no additional somatic mutations, making it a prototypical form of cancer whose adaptation to microenvironments is likely driven by acute, non-genomic mechanisms. Using computer vision analysis of 3D cell shapes, we find systematic shifts in the distribution of cell morphotypes between distinct sites in the fish embryo. We also find site-specific morphological responses to differential expression of EWSR1-FLI1. Combining these data we propose a model where Ewing Sarcoma cancer cell plasticity is sensitive both to expression fluctuation of EWSR1-FLI1 and signals from the surrounding tissue microenvironment, with either or both factors possibly contributing to the oncogenic potential of these cells. 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. Social integration predicts survival in female white-faced capuchin monkeys Across multiple species of social mammals, a growing number of studies have found that that individual sociality is associated with survival. In long-lived species, like primates, lifespan is one of the main components of fitness. We used 18 years of data from the Lomas Barbudal Monkey project to quantify social integration in 11 capuchin (Cebus capucinus) groups and tested whether female survivorship was associated with females tendencies to interact with three types of partners: (1) all group members, (2) adult females, (3) adult males. We found strong evidence that females who engaged more with other females in affiliative interactions and foraged in close proximity experienced increased survivorship. We found some weak evidence that females might also benefit from engaging in more support in agonistic contexts with other females. These benefits were evident in models that account for the females rank and group size. Female interactions with all group members also increased survival, but the estimates of the effects were more uncertain. In interactions with adult males, only females who provided more grooming to males survived longer. The results presented here suggest that social integration may result in survival-related benefits. Females might enjoy these benefits through exchanging grooming for other currencies, such as coalitionary support or tolerance. Pax6 loss alters the morphological and electrophysiological development of mouse prethalamic neurons Pax6 is a well-known regulator of early neuroepithelial progenitor development. Its constitutive loss has a particularly strong effect on the developing prethalamus, causing it to become extremely hypoplastic. To overcome this difficulty in studying the long-term consequences of Pax6 loss for prethalamic development, we used conditional mutagenesis to delete Pax6 at the onset of neurogenesis and studied the developmental potential of the mutant prethalamic neurons in vitro. We found that Pax6 loss affected their rates of neurite elongation, the location and length of their axon initial segments and their electrophysiological properties. Our results broaden our understanding of the long-term consequences of Pax6 deletion in the developing mouse forebrain, suggesting that it can have cell autonomous effects on the structural and functional development of some neurons.

SUMMARY STATEMENTPax6 impacts neurite extension, axon initial segment properties and ability to fire normal action potentials in maturing neurons, revealing actions extending beyond those previously characterized in progenitors. Soil inoculum identity and rate jointly steer microbiomes and plant communities in the field The importance of soil inoculation to engineer soil microbiomes and ultimately entire ecosystems is becoming widely acknowledged. Inoculation with soil from different ecosystems can induce directional changes in soil and plant communities and promote the restoration of degraded ecosystems. However, it is unknown how such inoculations influence the soil microbiome, how much inoculum is needed, and whether inocula collected from similar ecosystems will steer the microbiome in different directions. We conducted a three-year soil inoculation field experiment at a degraded grassland and used two different soil inocula both from grasslands with three inoculation rates. Our results show that inoculation with soil that originates from different donor grasslands steers the soil microbiome as well as the plant communities at the inoculated site which was a degraded grassland into different directions and that these effects were stronger with increasing amount of soil used to inoculate. Inoculation with upland meadow soil introduced more keystone genera and resulted in more complex biotic networks in the soil than inoculation with meadow steppe soil. Our experiment highlights that soil inoculation can steer soil microbiomes in the field and that the direction and speed of development depend on the origin and the amount of soil inoculum used.