Untargeted metabolomic analyses reveal the diversity and plasticity of the specialized metabolome in seeds of different Camelina sativa genotypes Despite the essential role of Specialized Metabolites (SMs) in the interaction of plants with the environment, studying the ability of crop seeds to produce these protective compounds has been neglected. Furthermore, seeds produce a myriad of SMs providing an interesting model to investigate their diversity and plasticity. Camelina sativa gained a lot of interest in the past few years as rustic oil seed crop. A characterization of seed SM landscapes in six camelina genotypes grown in the field and harvested during five growing seasons has been undertaken in this work. This allowed a comprehensive annotation of seed SMs combining analyses that cluster SMs based on their chemical structures and co-accumulation patterns. These data showed broad effects of the environment on the stimulation of the seed-specialized metabolome. Among well annotated compounds, flavonols were identified as the metabolic class characterised by high plasticity, revealing significant variable accumulation according to the year and/or the genotype. Lastly, a deeper characterisation of primary metabolites and lipids in two selected genotypes has been performed. We showed that, in addition to flavonols, alkaloids and glucosinolates displayed a higher phenotypic plasticity with respect to most of the primary metabolites, including some sugars and major storage compounds such as fatty acids, proteins and most lipid classes (e.g. DAG, TAG), but similar plasticity compared to free aminoacids and carboxylic acids. This work highlighted major and unexplored effects of the environment on the seed specialized metabolome demonstrating that seeds exhibit a dynamic and plastic metabolism, with an impact on seed quality.

Significance statementSeeds produce a myriad of Specialized Metabolites (SMs) with an essential role in the interaction of plants with the environment. We characterized SM landscapes, primary metabolites and lipid composition in the seeds of camelina genotypes grown in the open field in five consecutive growing seasons. Our results showed the predominant effect of the environment on the regulation of the seed - specialized metabolome, with a potential impact on seed quality of camelina that may also occur in other oilseed crops.
Applications of the indole-alkaloid gramine modulate the assembly of individual members of the barley rhizosphere microbiota Microbial communities proliferating at the root-soil interface, collectively referred to as the rhizosphere microbiota, represent an untapped beneficial resource for plant growth, development and health. Integral to a rational manipulation of the microbiota for sustainable agriculture is the identification of the molecular determinants of these communities. In plants, biosynthesis of allelochemicals is centre stage in defining inter-organismal relationships in the environment. Intriguingly, this process has been moulded by domestication and breeding selection. The indole-alkaloid gramine, whose occurrence in barley (Hordeum vulgare L.) is widespread among wild genotypes but has been counter selected in several modern varieties, is a paradigmatic example of this phenomenon. This prompted us to investigate how exogenous applications of gramine impacted on the rhizosphere microbiota of two, gramine-free, elite barley varieties grown in a reference agricultural soil. High throughput 16S rRNA gene amplicon sequencing revealed that applications of gramine interfere with the proliferation of a subset of soil microbes with a relatively broad phylogenetic assignment. Strikingly, growth of these bacteria appeared to be rescued by barley plants in a genotype- and dosage-independent manner. In parallel, we discovered that host recruitment cues can interfere with the impact of gramine application in a host genotype-dependent manner. Interestingly, this latter effect displayed a bias for members of the phyla Proteobacteria. These initial observations indicate that gramine can act as a determinant of the prokaryotic communities inhabiting the root-soil interface.
Gut bacteria regulate the pathogenesis of Huntington's disease in Drosophila model Changes in the composition of gut microbiota are implicated in the pathogenesis of several neurodegenerative disorders. Here, we investigated whether gut bacteria affect the progression of Huntingtons disease (HD) in transgenic Drosophila melanogaster (fruit fly) models expressing human full-length or N-terminal fragments of mutant huntingtin (HTT) protein, here referred to as HD flies. We find that elimination of commensal gut bacteria by antibiotics reduces the aggregation of amyloidogenic N-terminal fragments of HTT and delays the development of motor defects. Conversely, colonization of HD flies with Escherichia coli (E. coli), a known pathobiont of human gut with links to neurodegeneration, accelerates HTT aggregation, aggravates immobility and shortens lifespan. Similar to antibiotics, treatment of HD flies with small compounds such as luteolin, a flavone, or crocin a beta-carotenoid, ameliorates disease phenotypes and promotes survival. Crocin prevents colonization of E. coli in the gut and alters the abundance of commensal bacteria, which may be linked to its protective effects. The opposing effects of E. coli and crocin on HTT aggregation, motor defects and survival in transgenic Drosophila models support the involvement of gut-brain networks in the pathogenesis of HD. Robust retrieval of data stored in DNA by de Bruijn graph-based de novo strand assembly DNA data storage is a rapidly developing technology with great potential due to its high density, long-term durability, and low maintenance cost. The major technical challenges include various errors, such as the strand breaks, rearrangements, and indels that frequently arise during DNA synthesis, amplification, sequencing, and preservation. Through a de novo assembly strategy, we developed an algorithm based on the de Bruijn graph and greedy path search (DBGPS) to address these issues. DBGPS shows distinct advantages in handling DNA breaks, rearrangements, and indels. The robustness of DBGPS is demonstrated by accelerated aging, multiple independent data retrievals, deep error-prone PCR, and large data scale simulations. Remarkably, 6.8 MB of data can be retrieved accurately from a seriously corrupted sample that has been treated at 70 {degrees}C for 70 days. With DBGPS, we were able to achieve a logical density of 1.30 bits/cycle and a physical density of 295 PB/g.

One-Sentence SummaryA de Bruijn graph-based de novo assembly algorithm for DNA data storage enables fast and robust data readouts even with DNA samples that have been severely corrupted. Characterization of divalent cation interactions with AASTY native nanodiscs Amphiphilic copolymers show promise in extracting membrane proteins directly from lipid bilayers into  native nanodiscs. However, many such copolymers are polyanionic and sensitive to divalent cations, limiting their applicability. We characterize the Ca2+ and Mg2+ sensitivity of poly(acrylic acid-co-styrene) (AASTY) copolymers with analytical UV and fluorescent size exclusion chromatography, enabling us to separate signals from nanodiscs, copolymers, and soluble aggregates. We find that divalent cations promote aggregation and precipitation of both free and lipid bound copolymers. We see that excess, free copolymer acts as a  cation sink that protects nanodiscs from Ca2+ induced aggregation. Removal of the free copolymer through dialysis induces aggregation that can be mitigated by KCl. Finally, we find that the nanodisc size is dynamic and dependent on lipid concentration. Our results offer insight to nanodisc behaviour, and can help guide experimental design, aimed at mitigating the shortcomings inherent in negatively charged nanodisc forming copolymers. Omicron escapes the majority of existing SARS-CoV-2 neutralizing antibodies The SARS-CoV-2 B.1.1.529 variant (Omicron) contains 15 mutations on the receptor-binding domain (RBD). How Omicron would evade RBD neutralizing antibodies (NAbs) requires immediate investigation. Here, we used high-throughput yeast display screening1,2 to determine the RBD escaping mutation profiles for 247 human anti-RBD NAbs and showed that the NAbs could be unsupervised clustered into six epitope groups (A-F), which is highly concordant with knowledge-based structural classifications3-5. Strikingly, various single mutations of Omicron could impair NAbs of different epitope groups. Specifically, NAbs in Group A-D, whose epitope overlap with ACE2-binding motif, are largely escaped by K417N, G446S, E484A, and Q493R. Group E (S309 site)6 and F (CR3022 site)7 NAbs, which often exhibit broad sarbecovirus neutralizing activity, are less affected by Omicron, but still, a subset of NAbs are escaped by G339D, N440K, and S371L. Furthermore, Omicron pseudovirus neutralization showed that single mutation tolerating NAbs could also be escaped due to multiple synergetic mutations on their epitopes. In total, over 85% of the tested NAbs are escaped by Omicron. Regarding NAb drugs, the neutralization potency of LY-CoV016/LY-CoV555, REGN10933/REGN10987, AZD1061/AZD8895, and BRII-196 were greatly reduced by Omicron, while VIR-7831 and DXP-604 still function at reduced efficacy. Together, data suggest Omicron would cause significant humoral immune evasion, while NAbs targeting the sarbecovirus conserved region remain most effective. Our results offer instructions for developing NAb drugs and vaccines against Omicron and future variants. Kinetics and Mechanism of Fentanyl Dissociation from the mu-Opioid Receptor Driven by illicit fentanyl, opioid related deaths have reached the highest level in 2020. Currently, an opioid over-dose is resuscitated by the use of naloxone, which competitively binds and antagonizes the {micro}-opioid receptor (mOR). Thus, knowledge of the residence times of opioids at mOR and the unbinding mechanisms is valuable for assessing the effectiveness of naloxone. In the present study we calculate the fentanyl-mOR dissociation time and elucidate the mechanism by applying an enhanced sampling molecular dynamics (MD) technique. Two sets of metadynamics simulations with different initial structures were performed while accounting for the protonation state of the conserved H2976.52, which has been suggested to modulate the ligand-mOR affinity and binding mode. Surprisingly, with the N{delta}-protonated H2976.52, fentanyl can descend as much as 10 [A] below the level of the conserved D1473.32 before escaping the receptor, and has a calculated residence time{tau} of 38 s. In contrast, with the N - and doubly protonated H2976.52, the calculated{tau} are 2.6 s and 0.9 s, respectively. Analysis suggests that formation of the piperidine-Hid297 hydrogen bond strengthens the hydrophobic contacts with the transmembrane helix (TM) 6, allowing fentanyl to explore a deep pocket. Considering the experimental{tau} of [~]4 min for fentanyl and the role of TM6 in mOR activation, we suggest that the deep insertion mechanism may be biologically relevant. The work paves the way for large-scale computational predictions of opioid dissociation rates to inform the regulatory decision. The profound role of the histidine protonation state found here may shift the paradigm in computational studies of ligand-receptor kinetics. Comparing genome-based estimates of relatedness for use in pedigree-based conservation management Researchers have long debated which estimator of relatedness best captures the degree of relationship between two individuals. In the genomics era, this debate continues, with relatedness estimates being sensitive to the methods used to generate markers, marker quality, and levels of diversity in sampled individuals. Here, we compare six commonly used genome-based relatedness estimators (kinship genetic distance (KGD), Wang Maximum Likelihood (TrioML), Queller and Goodnight (Rxy), Kinship INference for Genome-wide association studies (KING-robust), and Pairwise Relatedness (RAB), allele-sharing co-ancestry (AS)) across five species bred in captivity-including three birds and two mammals-with varying degrees of reliable pedigree data, using reduced-representation and whole genome resequencing data. Genome-based relatedness estimates varied widely across estimators, sequencing methods, and species, yet the most consistent results for known first order relationships were found using Rxy, RAB, and AS. However, AS was found to be less consistently correlated with known pedigree relatedness than either Rxy or RAB. Our combined results indicate there is not a single genome-based estimator that is ideal across different species and data types. To determine the most appropriate genome-based relatedness estimator for each new dataset, we recommend assessing the relative: (1) correlation of candidate estimators with known relationships in the pedigree and (2) precision of candidate estimators with known first-order relationships. These recommendations are broadly applicable to conservation breeding programs, particularly where genome-based estimates of relatedness can complement and complete poorly pedigreed populations. Given a growing interest in the application of wild pedigrees, our results and are also applicable to in-situ wildlife management. Intervene or wait? A model evaluating the timing of intervention in conservation conflicts adaptive management under uncertainty. The timing of biodiversity managers interventions can be critical to the success of conservation, especially in situations of conflict between conservation objectives and human livelihood, i.e., conservation conflicts. Given the uncertainty associated with complex social-ecological systems and the potentially irreversible consequences of delayed action for biodiversity and livelihoods, managers tend to simply intervene as soon as possible by precaution. However, refraining from intervening when the situation allows it can be beneficial, notably by saving critical management resources. Here, we introduce a strategy for managers to decide, based on monitoring, whether intervention is required or if waiting is possible. This study evaluates the performance of this waiting strategy compared to a strategy of unconditional intervention at every opportunity. We built an individual-based model of conservation conflict between a manager aiming to conserve an animal population and farmers aiming to maximize yield by protecting their crop from wildlife damage. We then simulated a budget-constrained adaptive management over time applying each strategy, while accounting for uncertainty around population dynamics and around decision-making of managers and farmers. Our results showed that when the decision for the manager to intervene was based on a prediction of population size trajectory, the waiting strategy performed at least as well as unconditional intervention while also allowing managers to save resources by avoiding unnecessary interventions. Under difficult budgetary constraints on managers, this waiting strategy ensured as high yields as unconditional intervention while significantly improving conservation outcomes by compensating managers lack of resources with the benefits accrued over waiting periods. This suggests that waiting strategies are worth considering in conservation conflicts, as they can facilitate equitable management with a more efficient use of management resources, which are often limiting in biodiversity conservation. Signatures of Discriminative Copy Number Aberrations in 31 Cancer Subtypes Copy number aberrations (CNA) are one of the most important classes of genomic mutations related to oncogenetic effects. In the past three decades, a vast amount of CNA data has been generated by molecular-cytogenetic and genome sequencing based methods. While this data has been instrumental in the identification of cancer-related genes and promoted research into the relation between CNA and histo-pathologically defined cancer types, the heterogeneity of source data and derived CNV profiles pose great challenges for data integration and comparative analysis. Furthermore, a majority of existing studies have been focused on the association of CNA to pre-selected "driver" genes with limited application to rare drivers and other genomic elements.

In this study, we developed a bioinformatics pipeline to integrate a collection of 44,988 high-quality CNA profiles of high diversity. Using a hybrid model of neural networks and attention algorithm, we generated the CNA signatures of 31 cancer subtypes, depicting the uniqueness of their respective CNA landscapes. Finally, we constructed a multi-label classifier to identify the cancer type and the organ of origin from copy number profiling data. The investigation of the signatures suggested common patterns, not only of physiologically related cancer types but also of clinico-pathologically distant cancer types such as different cancers originating from the neural crest. Further experiments of classification models confirmed the effectiveness of the signatures in distinguishing different cancer types and demonstrated their potential in tumor classification. High performance single-cell gene regulatory network inference atscale: The Inferelator 3.0 MotivationGene regulatory networks define regulatory relationships between transcription factors and target genes within a biological system, and reconstructing them is essential for understanding cellular growth and function. Methods for inferring and reconstructing networks from genomics data have evolved rapidly over the last decade in response to advances in sequencing technology and machine learning. The scale of data collection has increased dramatically; the largest genome-wide gene expression datasets have grown from thousands of measurements to millions of single cells, and new technologies are on the horizon to increase to tens of millions of cells and above.

ResultsIn this work, we present the Inferelator 3.0, which has been significantly updated to integrate data from distinct cell types to learn context-specific regulatory networks and aggregate them into a shared regulatory network, while retaining the functionality of the previous versions. The Inferelator is able to integrate the largest single-cell datasets and learn cell-type specific gene regulatory networks. Compared to other network inference methods, the Inferelator learns new and informative Saccharomyces cerevisiae networks from single-cell gene expression data, measured by recovery of a known gold standard. We demonstrate its scaling capabilities by learning networks for multiple distinct neuronal and glial cell types in the developing Mus musculus brain at E18 from a large (1.3 million) single-cell gene expression dataset with paired single-cell chromatin accessibility data.

AvailabilityThe inferelator software is available on GitHub (https://github.com/flatironinstitute/inferelator) under the MIT license and has been released as python packages with associated documentation (https://inferelator.readthedocs.io/). Erythropoietin supplementation ameliorates the immunological and hematological deficiencies of lysinuric protein intolerance in mice SLC7A7 encodes for y+LAT1, a cationic amino acid transporter expressed on the basolateral membrane of epithelial cells and macrophages. Mutations in human SLC7A7 cause lysinuric protein intolerance (LPI), a rare autosomal disorder with a variety of clinical symptoms. Citrulline and a low protein diet are widely used to treat the main symptoms of LPI; however, the hematological and immunological abnormalities in LPI remain poorly understood and difficult to manage by established treatments. Here, we show that erythropoietin levels are significantly diminished in mice lacking Slc7a7, which reduces the number of erythroblast precursors, resulting in mature red blood cells with a smaller mean corpuscular volume. Ex vivo analysis demonstrated that erythrocytes from Slc7a7-deficient mice were phagocytosed more by bone marrow-derived macrophages. Gene expression analysis of sorted red pulp macrophages (RPMs) from Slc7a7-deficient mice indicated that this cell population had higher erythrophagocytic activity, but preserved heme catabolic activity. The increase in erythrophagocytosis resulted in iron accumulation in macrophages and tissues, and ultimately led to RPM apoptosis. Surprisingly, ablation of Slc7a7 in myeloid cells failed to trigger tissue iron accumulation or changes in the RPM population, indicating that the expression of this gene in macrophages is not key for the development of iron accumulation in tissue. Finally, restoration of serum erythropoietin levels in Slc7a7-deficient mice re-established normal erythropoiesis and erythrophagocytosis and prevented the accumulation of iron in tissues. Thus, erythropoietin has a fundamental role in the immune-hematological alterations of LPI in mice, revealing a new crucial role for this hormone in this disease. Naming Human Diseases: Ethical Principles of Curating Exclusive Substitute for Inopportune Nosology BackgroundIn the medical sphere, understanding naming conventions strengthen the integrity of naming human diseases remains nominal rather than substantial yet. Since the current nosology-based standard for human diseases could not offer a one-size-fits-all corrective mechanism, many idiomatic but flawed names frequently appear in scientific literature and news outlets at the cost of sociocultural impacts.

ObjectiveWe attempt to examine the ethical oversights of current naming practices and propose heuristic rationales and approaches to determine a pithy name instead of an inopportune nosology.

MethodsFirst, we examined the compiled global online news volumes and emotional tones on some inopportune nosology like German measles, Middle Eastern Respiratory Syndrome, Spanish flu, Hong Kong flu, and Huntingtons disease in the wake of COVID-19. Second, we prototypically scrutinize the lexical dynamics and pathological differentials of German measles and common synonyms by leveraging the capacity of the Google Books Ngram Corpus. Third, we demonstrated the empirical approaches to curate an exclusive substitute for an anachronistic nosology German measles based on deep learning models and post-hoc explanations.

ResultsThe infodemiological study shows that the public informed the offensive names with extremely negative tones in textual and visual narratives. The findings of the historiographical study indicate that many synonyms of German measles did not survive, while German measles became an anachronistic usage, and rubella has taken the dominant place since 1994. The PubMedBERT model could identify rubella as a potential substitution for German measles with the highest semantic similarity. The results of the semantic drift experiments further indicate that rubella tends to survive during the ebb and flow of semantic drift.

ConclusionsOur findings indicate that the nosological evolution of anachronistic names could result in sociocultural impacts without a corrective mechanism. To mitigate such impacts, we introduce some ethical principles for formulating an improved naming scheme. Based on deep learning models and post-hoc explanations, our illustrated experiments could provide hallmark references to the remedial mechanism of naming practices and pertinent credit allocations. Non-Newtonian Blood Rheology Impacts Left Atrial Stasis in Patient-Specific Simulations The lack of mechanically effective contraction of the left atrium (LA) during atrial fibrillation (AF) disturbs blood flow, increasing the risk of thrombosis and ischemic stroke. Thrombosis is most likely in the left atrial appendage (LAA), a small narrow sac where blood is prone to stagnate. Slow flow promotes the formation of erythrocyte aggregates in the LAA, also known as rouleaux, causing viscosity gradients that are usually disregarded in patient-specific simulations. To evaluate these non-Newtonian effects, we built atrial models derived from 4D computed tomography scans of patients and carried out computational fluid dynamics simulations using the Carreau-Yasuda constitutive relation. We examined six patients, three of whom had AF and LAA thrombosis or a history of transient ischemic attacks (TIAs). We modeled the effects of hematocrit and rouleaux formation kinetics by varying the parameterization of the Carreau-Yasuda relation and modulating non-Newtonian viscosity changes based on residence time. Comparing non-Newtonian and Newtonian simulations indicates that slow flow in the LAA increases blood viscosity, altering secondary swirling flows and intensifying blood stasis. While some of these effects can be subtle when examined using instantaneous metrics like shear rate or kinetic energy, they are manifested in the blood residence time, which accumulates over multiple heartbeats. Our data also reveal that LAA blood stasis worsens when hematocrit increases, offering a potential new mechanism for the clinically reported correlation between hematocrit and stroke incidence. In summary, we submit that hematocrit-dependent non-Newtonian blood rheology should be considered in calculating patient-specific blood stasis indices by computational fluid dynamics. Influence of DNA extraction kits on freshwater fungal DNA metabarcoding BackgroundEnvironmental DNA (eDNA) metabarcoding is a common technique for efficient biodiversity monitoring, especially of microbes. Recently, the usefulness of aquatic eDNA in monitoring the diversity of both terrestrial and aquatic fungi has been suggested. In eDNA studies, different experimental factors, such as DNA extraction kits or methods, can affect the subsequent analyses and the results of DNA metabarcoding. However, few methodological studies have been carried out on eDNA of fungi, and little is known about how experimental procedures can affect the results of biodiversity analysis. In this study, we focused on the effect of DNA extraction method on fungal DNA metabarcoding using freshwater samples obtained from rivers and lakes.

MethodsDNA was extracted from freshwater samples using the DNeasy PowerSoil kit, which is mainly used to extract microbial DNA from soil, and the DNeasy Blood & Tissue kit, which is commonly used for eDNA studies on animals. We then compared PCR inhibition and fungal DNA metabarcoding results; i.e., operational taxonomic unit (OTU) number and composition of the extracted samples.

ResultsNo PCR inhibition was detected in any of the samples, and no significant differences in the number of OTUs and OTU compositions were detected between the samples processed using different kits. These results indicate that both DNA extraction kits may provide similar diversity results for the river and lake samples evaluated in this study. Therefore, it may be possible to evaluate the diversity of fungi using a unified experimental method, even with samples obtained for diversity studies on other taxa such as those of animals. Feed efficiency of lactating Holstein cows was not as repeatable across diets as within diet over subsequent lactation stages BackgroundImproving feed efficiency has become a common target for dairy farmers to meet the requirement of producing more milk with fewer resources. To improve feed efficiency, a prerequisite is to ensure that the cows identified as most or least efficient will remain as such, independently of diet composition. Therefore, the current research analysed the ability of lactating dairy cows to maintain their feed efficiency while changing the energy density of the diet by changing its concentration in starch and fibre. A total of 60 lactating Holstein cows, including 33 primiparous cows, were first fed a high starch diet-low fibre (diet S+F-), then switched over to a low starch diet-high fibre (diet S-F+). To know if diet affect feed efficiency, we compared the ability of feed efficiency to be maintained within a diet over subsequent lactation stages, known as repeatability of feed efficiency, with its ability to be maintained across diets, known as reproducibility of feed efficiency. To do so we used two indicators: the estimation of the error of repeatability/reproducibility, which is commonly used in metrology, and the coefficient of correlation of concordance (CCC), which is used in biology. The effect of diet change could also lead to a change in cows sorting behaviour which could potentially affect feed efficiency if for example the most efficient cows select more concentrate than the least efficient. We therefore analysed the relationship between the differences in individual feed refusals composition and the differences in feed efficiency. To do so, the composition of each feed refusal was described with its near infra-red (NIR) spectroscopy and was performed on each individual feed ingredient, diet and refusals and used as composition variable. The variability of the NIR spectra of the refusals was described with its principal components thanks to a principal component analysis (PCA). The Pearson correlation was estimated to check the relationship between feed efficiency and refusals composition, i.e. sorting behaviour.

ResultsThe error of reproducibility of feed efficiency across diets was 2.95 MJ/d. This error was significantly larger than the errors of repeatability estimated within diet, which were 2.01 MJ/d within diet S-F+ and 2.40 MJ/d within diet S+F-. The CCC was 0.64 between feed efficiency estimated within diet S+F- and feed efficiency estimated within diet S-F+. This CCC was smaller than the one observed for feed efficiency estimated within diet between two subsequent lactation stages (CCC = 0.72 within diet S+F- and 0.85 within diet S-F+). Feed efficiency was poorly correlated to the first two principal components, which explained 90% of the total variability of the NIR spectra of the individual refusals. This suggests that feed sorting behaviour did not explain differences in feed efficiency.

ConclusionsFeed efficiency was significantly less reproducible across diets than repeatable within the same diet over subsequent lactation stages, but cows ranking for feed efficiency was not significantly affected by diet change. This loss in repeatability across diets could be due to a more pronounced feed sorting subsequent to the change in diet composition. However, the differences in sorting behaviour between cows were not associated to feed efficiency differences in this trial neither with the S+F- diet nor with the S-F+ diet. Those results have to be confirmed on diets having different forage to concentrate ratios to ensure that the least and most efficient cows will not change. Deep learning can predict multi-omic biomarkers from routine pathology images: A systematic large-scale study We assessed the pan-cancer predictability of multi-omic biomarkers from haematoxylin and eosin (H&E)-stained whole slide images (WSI) using deep learning (DL) throughout a systematic study. A total of 13,443 DL models predicting 4,481 multi-omic biomarkers across 32 cancer types were trained and validated. The investigated biomarkers included a broad range of genetic, transcriptomic, proteomic, and metabolic alterations. Furthermore, established markers relevant for prognosis, molecular subtypes and clinical outcomes were included. Overall, we established the general feasibility of predicting multi-omic markers directly from routine histology images with DL across solid cancer types, where 50% of the models could perform at an area under the curve (AUC) of more than 0.633 (with 25% of the models having an AUC larger than 0.711). A wide range of biomarkers were detectable from routine histology images across all investigated cancer types, with a mean AUC of at least 0.62 in almost all malignancies. Strikingly, we observed that biomarker predictability was mostly consistent and not dependent on sample size and class ratio, suggesting a degree of true predictability inherent in histomorphology. Together, the results of our study show the potential of DL to predict a multitude of biomarkers across the omics spectrum using only routine slides. This paves the way for accelerating diagnosis and developing more precise treatments for cancer patients. Inhibition of microbial deconjugation of micellar bile acids protects against intestinal permeability and liver injury Altered host-microbe interactions and increased intestinal permeability have been implicated in the pathogenesis of a range of diseases. However, the mechanisms by which gut microbes affect epithelial barrier integrity remain unclear. Few host-produced metabolites that protect against epithelial damage have been identified, and whether microbial metabolism of host factors alters intestinal barrier function is unknown. Here, we investigate the effects of bacterial metabolism of host-produced bile acid (BA) metabolites on epithelial barrier integrity. We observe that rats fed a choline-deficient, high-fat diet (CDAHFD) exhibit reduced abundance of host-produced conjugated BAs in the intestine at early timepoints coinciding with increased permeability. We show that in vitro, conjugated BAs protect gut epithelial monolayers from damage caused by bacterially produced unconjugated BAs through micelle formation. We then demonstrate that inhibition of BA deconjugation using a small molecule inhibitor of gut bacterial bile salt hydrolase (BSH) enzymes prevents development of pathologic intestinal permeability and hepatic inflammation in CDAHFD-fed rats. Finally, we show that the predominant conjugated BAs in humans protect against epithelial barrier disruption in vitro. Our study identifies a protective role for conjugated BAs in intestinal epithelial barrier function and suggests that rational manipulation of microbial BA metabolism could be leveraged to regulate gut barrier integrity. Polycystins are upregulated in fibrotic kidneys and promote renal fibrosis Autosomal polycystic kidney disease (ADPKD) is caused by mutations in PKD1or PKD2 gene, which encodes polycystin-1 or polycystin-2 respectively. Paradoxically, polycystins are up-regulated in human ADPKD kidneys and overexpression of polycystin-1 even induced renal cyst formation in mice, suggesting that up-regulation of polycystin is pathogenic. In this study, we determined the role of polycystin in renal fibrosis and explored its underlying mechanisms. We found that the expression of polycystin-1 or polycystin-2 was positively correlated with the expression of collagen-I in the kidney of three different fibrotic mouse models. Pharmaceutical inhibition or genetic knockout of polycystin-2 reduced the expression of pro-fibrotic markers in fibrotic kidneys of two animal models. Moreover, conditional knockout of Pkd1 gene attenuated renal fibrosis in two mouse models. Enhancer of Zeste homolog 2 (EZH2) is a methyltransferase which plays important role in renal fibrosis. We found that EZH2 was positively correlated with the expression of polycystins in fibrotic kidneys. Conditional knockout of the Ezh2 attenuated the anti-fibrotic responses induced by Pkd1 deletion in fibrotic kidneys.

In conclusion, polycystins are up-regulated in injured kidneys and polycystins promote renal fibrosis through up-regulation of EZH2 in fibrotic kidneys, suggesting that renal fibrosis in polycystic kidneys is not the direct effect of PKD gene mutations.

SignificanceMutations of polycystins cause autosomal polycystic kidney disease (ADPKD) which is associated with increased renal fibrosis in cystic kidneys. However, the role of polycystin in renal fibrosis remains unclear. Here, we showed that the expression of polycystins is positively correlated with the development of renal fibrosis in injured kidneys. Pharmaceutical inhibition or genetic deletion of polycystin-2 attenuated renal fibrosis in fibrotic kidneys. Moreover, genetic deletion of polycystin-1 inhibited renal fibrosis in two different animal models. Finally, we showed that ablation of the methyltransferase EZH2 mitigated the anti-fibrotic effect of polycystin-1 deletion in fibrotic kidneys. We conclude that polycystin promotes through EZH2 and renal fibrosis in cystic kidney is not the direct effect of PKD gene mutations. Cell trajectory modeling identifies a primitive trophoblast state defined by BCAM enrichment In early placental development, progenitor cytotrophoblasts (CTBs) differentiate along one of two cellular trajectories: the villous or extravillous pathways. CTBs committed to the villous pathway fuse with neighboring CTBs to form the outer multinucleated syncytiotrophoblast (SCT), while CTBs committed to the extravillous pathway differentiate into invasive extravillous trophoblasts (EVT). Unfortunately, little is known about the processes controlling human CTB progenitor maintenance and differentiation. To address this, we established a single cell RNA sequencing (scRNA-seq) dataset from first trimester placentas to identify cell states important in trophoblast progenitor establishment, renewal, and differentiation. Multiple distinct trophoblast states were identified, representing progenitor CTBs, column CTBs, SCT precursors, and EVT. Lineage trajectory analysis identified a progenitor origin that was reproduced in human trophoblast stem cell organoids. Heightened expression of basal cell adhesion molecule (BCAM) defined this primitive state, where BCAM enrichment or gene silencing resulted in enhanced or diminished organoid growth. Together, this work describes at high-resolution trophoblast heterogeneity within the first trimester, resolves gene networks within human CTB progenitors, and identifies BCAM as a primitive progenitor marker and possible regulator.

Summary StatementLineage trajectory modeling identifies multiple human progenitor trophoblast states and defines trophoblast differentiation kinetics, where BCAM-expressing progenitors demonstrate enhanced regenerative ability. Venomics and antivenomics of Indian spectacled cobra (Naja naja) from the Western Ghats Venom proteome profiling of Naja naja from the Western Ghats region in Kerala was achieved through SDS-PAGE and RP-HPLC followed by Q-TOF LC-MS/MS analysis, incorporating PEAKS and Novor assisted de novo sequencing methodologies. A total of 115 proteins distributed across 17 different enzymatic and non-enzymatic venom protein families were identified through conventional and 39 peptides through homology-driven proteomics approaches. Fourteen peptides derived through de novo complements the Mascot data indicating the importance of homology-driven approaches in improving protein sequence information. Among the protein families identified, glutathione peroxidase and endonuclease were reported for the first time in the Indian cobra venom. Immunological cross-reactivity assessed using Indian polyvalent antivenoms suggested that VINS showed better EC50 (2.48 g/mL) value than that of PSAV (6.04 g/mL) and Virchow (6.03 g/mL) antivenoms. Western blotting experiments indicated that all the antivenoms elicited poor binding specificities, especially towards low molecular mass proteins. Second-generation antivenomics studies revealed that VINS antivenom was less efficient to detect many low molecular mass proteins such as three-finger toxins and Kunitz-type serine protease Inhibitors. Taken together, the present study enabled a large-scale characterization of the venom proteome of Naja naja from the Western Ghats and emphasized the need for developing more efficient antivenoms.

HighlightsO_LIProteomics of cobra venom resulted in the identification of 115 proteins representing 17 snake venom protein families.
C_LIO_LIDe novo approaches exclusively yielded 39 peptides harbouring multiple amino acid mutations.
C_LIO_LIGlutathione peroxidase and endonuclease were identified for the first time in Indian cobra venom.
C_LIO_LIIndian polyvalent antivenoms showed varying cross-reactivity towards cobra venom.
C_LIO_LIVINS antivenom was less efficient to detect many low molecular mass proteins (< 20 kDa).
C_LI wnt16 exerts pleiotropic effects on bone and lean mass in zebrafish Osteoporosis, a disease of bone fragility, and sarcopenia, a condition of reduced muscle mass and strength, commonly occur in the same individual--a condition termed osteosarcopenia. Genetic variants at the CPED1-WNT16 locus have pleiotropic effects on human bone mineral density (BMD) and lean tissue mass. However, our current understanding of Wnt16 and its influence on bone fails to explain effects on lean mass at this locus. In this study, we sought to better understand the biological mechanism underlying pleiotropy at the CPED1-WNT16 locus on BMD and lean mass. Using single cell analysis, microCT imaging, and genetic approaches in zebrafish, we show that wnt16 exerts dual influence on muscle and bone, and provide evidence that this occurs through a function in somite development, a period in which precursors for both of these tissues are specified. We show that mutations in wnt16 alter vertebral size and lean mass during axial skeletogenesis. We show that wnt16+ cells transcriptionally resemble cells within the amniote dermomyotome, and provide evidence they function as myogenic precursors during embryonic development. We also provide evidence that WNT16 is a gene of major effect on lean mass at the CPED-WNT16 locus. Our studies support the potential for wnt16 to exert pleiotropic effects on bone and lean mass through a function in myogenic precursors. Kaposi's sarcoma-associated herpesvirus (KSHV) utilizes the NDP52/CALCOCO2 selective autophagy receptor to disassemble processing bodies Kaposis sarcoma-associated herpesvirus (KSHV) causes the inflammatory and angiogenic endothelial cell neoplasm, Kaposis sarcoma (KS). We previously demonstrated that expression of the KSHV protein, Kaposin B (KapB), promoted inflammation via the disassembly of cytoplasmic ribonucleoprotein granules called processing bodies (PBs). Processing bodies (PBs) modify gene expression by silencing or degrading labile messenger RNAs (mRNAs) including many transcripts that encode inflammatory or angiogenic proteins that are associated with KS disease. Although our work implicated PB disassembly as one of the causes of inflammation during KSHV infection, the precise mechanism used by KapB to elicit PB disassembly was unclear. Here we reveal a new connection between the degradative process of autophagy and PB disassembly. We show that both latent KSHV infection and KapB expression enhanced autophagic flux via the phosphorylation of the autophagy regulatory protein, Beclin 1. KapB was necessary for this effect, as infection with a recombinant virus that does not express the KapB protein did not induce Beclin 1 phosphorylation or autophagic flux. Moreover, we reveal that PB disassembly mediated by KSHV or KapB depended on canonical autophagy genes and the selective autophagy receptor NDP52/CALCOCO2 and that the PB scaffolding protein, Pat1b, co-immunoprecipitated with NDP52. These studies reveal a new role for autophagy and the selective autophagy receptor NDP52 in promoting PB turnover and the concomitant synthesis of inflammatory molecules during KSHV infection.

Author SummaryKaposis sarcoma-associated herpesvirus (KSHV) is the causative agent of the inflammatory, endothelial cell cancer, Kaposis Sarcoma (KS). KSHV induces a pro-tumourigenic inflammatory environment which aids in the establishment and maintenance of the KS lesion. Processing bodies (PBs) are cellular structures that dampen inflammatory gene expression by suppression or decay of their cognate RNA molecules. We previously showed that the viral protein KapB caused PB disappearance during KSHV infection, identifying a new pathway used by KSHV to elicit inflammation. Now, we show that KSHV and KapB hijack the cellular degradative process of autophagy to promote PB disassembly and increase inflammatory gene expression. This places autophagy as central to the regulation of inflammation by KSHV and illustrates another remarkable strategy used by these viruses to create a tumourigenic microenvironment. Taxon-specific or universal? Using target capture to study the evolutionary history of rapid radiations Target capture has emerged as an important tool for phylogenetics and population genetics in non-model taxa. Whereas developing taxon-specific capture probes requires sustained efforts, available universal kits may have a lower power to reconstruct relationships at shallow phylogenetic scales and within rapidly radiating clades. We present here a newly-developed target capture set for Bromeliaceae, a large and ecologically-diverse plant family with highly variable diversification rates. The set targets 1,776 coding regions, including genes putatively involved in key innovations, with the aim to empower testing of a wide range of evolutionary hypotheses. We compare the relative power of this taxon-specific set, Bromeliad1776, to the universal Angiosperms353 kit. The taxon-specific set results in higher enrichment success across the entire family, however, the overall performance of both kits to reconstruct phylogenetic trees is relatively comparable, highlighting the vast potential of universal kits for resolving evolutionary relationships. For more detailed phylogenetic or population genetic analyses, e.g. the exploration of gene tree concordance, nucleotide diversity or population structure, the taxon-specific capture set presents clear benefits. We discuss the potential lessons that this comparative study provides for future phylogenetic and population genetic investigations, in particular for the study of evolutionary radiations. An epigenomic shift in amygdala marks the transition to maternal behaviors in alloparenting virgin female mice In many species, adults care for young offspring that are not their own, a phenomenon called alloparenting. However, most nonparental adults must be sensitized by repeated or extended exposures to newborns before they will robustly display parental-like behaviors. To capture neurogenomic events underlying the transition to active parental caring behaviors, we analyzed brain gene expression and chromatin profiles of virgin female mice co-housed with mothers during pregnancy and after birth. After an initial display of antagonistic behaviors and a surge of defense-related gene expression, we observed a dramatic shift in the chromatin landscape specifically in amygdala of the pup-exposed virgin females, accompanied by a dampening of anxiety-related gene expression. This epigenetic shift coincided with hypothalamic expression of the oxytocin gene and the emergence of behaviors and gene expression patterns classically associated with maternal care. The results outline a neurogenomic program associated with dramatic behavioral changes and suggest molecular networks relevant to human postpartum mental health. 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.