Visualization of bacterial type 3 secretion system components down to the molecular level by MINFLUX nanoscopy Type 3 secretion systems (T3SS) are essential virulence factors of numerous bacterial pathogens and inject effector proteins into host cells. The needle-like T3SS machinery consists of more than 20 components, has a length of around 100 nm and a diameter of up to 30 nm according to EM studies. Its intrabacterial components are highly dynamic and in permanent exchange with other bacterial structures. Therefore, a temporally and spatially resolved visualization of the T3SS using fluorescence microscopy techniques has been challenging. In the present study, novel labeling strategies were combined with super-resolution microscopy such as STED, STORM and MINFLUX. MINFLUX nanoscopy allowed to visualize components of the T3SS machinery such as the dynamic sorting platform component YscL and the extrabacterial pore protein YopD at unprecedented resolutions. The presented results represent the basis for an in depth investigation of T3SS structure and function and therefore gain new insights into the infection process of human pathogens in order to develop novel treatment and prevention strategies.
Artemisia annua L. extracts inhibit the in vitro replication of SARS-CoV-2 and two of its variants Ethnopharmacological relevanceArtemisia annua L. has been used for millennia in Southeast Asia to treat "fever". Many infectious microbial and viral diseases have been shown to respond to A. annua and communities around the world use the plant as a medicinal tea, especially for treating malaria.

Aim of the StudySARS-CoV-2 (the cause of Covid-19) globally has infected and killed millions of people. Because of the broad-spectrum antiviral activity of artemisinin that includes blockade of SARS-CoV-1, we queried whether A. annua suppressed SARS-CoV-2.

Materials and MethodsUsing Vero E6 and Calu-3 cells, we measured anti viral activity SARS-CoV-2 activity against fully infectious virusof dried leaf extracts of seven cultivars of A. annua sourced from four continents. IC50s were calculated and defined as (the concentrations that inhibited viral replication by 50%.) and CC50s (the concentrations that kill 50% of cells) were calculated.

ResultsHot-water leaf extracts based on artemisinin, total flavonoids, or dry leaf mass showed antiviral activity with IC50 values of 0.1-8.7 M, 0.01-0.14 g, and 23.4-57.4 g, respectively. Antiviral efficacy did not correlate with artemisinin or total flavonoid contents of the extracts. One dried leaf sample was >12 years old, yet the hot-water extract was still found to be active. The UK and South African variants, B1.1.7 and B1.351, were similarly inhibited. While all hot water extracts were effective, concentrations of artemisinin and total flavonoids varied by nearly 100-fold in the extracts. Artemisinin alone showed an estimated IC50 of about 70 M, and the clinically used artemisinin derivatives artesunate, artemether, and dihydroartemisinin were ineffective or cytotoxic at elevated micromolar concentrations. In contrast, the antimalarial drug amodiaquine had an IC50 = 5.8 M. Extracts had minimal effects on infection of Vero E6 or Calu-3 cells by a reporter virus pseudotyped by the SARS-CoV-2 spike protein. There was no cytotoxicity within an order of magnitude above the antiviral IC90 values.

ConclusionsA. annua extracts inhibit SARS-CoV-2 infection, and the active component(s) in the extracts is likely something besides artemisinin or a combination of components that block virus infection at a step downstream of virus entry. Further studies will determine in vivo efficacy to assess whether A. annua might provide a cost-effective therapeutic to treat SARS-CoV-2 infections.

List of compounds studiedAmodiaquine
Artemisinin
Artesunate
Artemether
Deoxyartemisinin
Dihydroartemisinin


HighlightsO_LIArtemisia annua is effective in stopping replication of SARS-CoV-2 including 2 new variants.
C_LIO_LIThe anti-viral effect does not correlate to artemisinin, nor to the total flavonoid content.
C_LIO_LIThe anti-viral mechanism does not appear to involve blockade virus entry into cell.
C_LIO_LIThe plant offers two additional benefits: a decreased inflammatory response and blunting of fibrosis.
C_LIO_LIA. annua may provide a safe, low-cost alternative for treating patients infected with SARS-CoV-2.
C_LI
A novel Fiji/ImageJ plugin for the rapid analysis of blebbing cells When confined, cells have recently been shown to undergo a phenotypic switch to what has been termed, fast amoeboid (leader bleb-based) migration. However, as this is a nascent area of research, few tools are available for the rapid analysis of cell behavior. Here, we demonstrate that a novel Fiji/ImageJ-based plugin, Analyze_Blebs, can be used to quickly obtain cell migration parameters and morphometrics from time lapse images. As validation, we show that Analyze_Blebs can detect significant differences in cell migration and morphometrics, such as the largest bleb size, upon introducing different live markers of F-actin, including F-tractin and LifeAct tagged with green and red fluorescent proteins. We also demonstrate, using flow cytometry, that live markers increase total levels of F-actin. Furthermore, that F-tractin increases cell stiffness, which was found to correlate with a decrease in migration, thus reaffirming the importance of cell mechanics as a determinant of Leader Bleb-Based Migration (LBBM).

Highlight summaryA new plugin, Analyze_Blebs, enables the rapid analysis of cell migration and morphometrics of fast amoeboid cells. Morphometrics combined with cell stiffness are found to be predictive of confined, fast amoeboid (leader bleb-based), migration. Critical re-evaluation of the slope factor of the operational model of agonism Background and PurposeAlthough being a relative term, agonist efficacy is a cornerstone in the proper assessment of agonist selectivity and signalling bias. The operational model of agonism (OMA) has become successful in the determination of agonist efficacies and ranking them. In 1985, Black et al. introduced the slope factor to the OMA to make it more flexible and allow for fitting steep as well as flat concentration-response curves.

Experimental ApproachFunctional analysis of OMA demonstrates that the slope factor implemented by Black et al. affects relationships among parameters of the OMA, leading to wrong estimates of operational efficacy and affinity of an agonist. In contrast, functional analysis of OMA with Hill coefficient as a slope factor has not this flaw.

Key ResultsFitting of the OMA with Black et al. slope factor to concentration-response curves of several models (homotropic allosteric modulation, substrate inhibition and non-competitive auto-inhibition) gives wrong estimates of operational efficacy and affinity. In contrast, fitting of the OMA modified by the Hill coefficient to concentration-response curves of these several models gives correct estimates of operational efficacy and affinity.

Conclusion and ImplicationsThe OMA modified by the Hill coefficient can be used for correct ranking of agonism and subsequent analysis, like quantification of signalling bias. Dimerization of kringle 1 domain from hepatocyte growth factor/scatter factor provides a potent minimal MET receptor agonist. Hepatocyte Growth Factor/Scatter Factor (HGF/SF) and its cognate receptor MET play several essential roles in embryogenesis and regeneration in post-natal life of epithelial organs such as liver, kidney, lung, and pancreas, prompting a strong interest in harnessing HGF/SF-MET signalling for regeneration of epithelial organs after acute or chronic damage. The limited stability and tissue diffusion of native HGF/SF, however, which reflect the tightly controlled, local mechanism of action of the morphogen, have led to a major search for HGF/SF mimics for therapy. In this work, we describe the rational design, production and characterisation of K1K1, a novel minimal MET agonist consisting of two copies of the kringle 1 domain of HGF/SF placed in tandem. K1K1 is highly stable and displays biological activities equivalent or superior to native HGF/SF in a variety of in vitro assay systems and in a mouse model of liver disease. These data suggest that this engineered ligand may find wide applications in acute and chronic diseases of the liver and other epithelial organs dependent on MET activation. Diurnal activity budget and conservation implication of Hippopotamus amphibius at Bui National Park, Ghana Animals apportion time for their daily behavioral activities. We studied the activity budget of Hippopotamus amphibius at the Black Volta River in the Bui National Park, Ghana. We performed instantaneous scan sample using ground count survey between August 2020 to July 2021. We observed that H. amphibius spent most of their day time resting (54.75 %), followed by feeding (22.93 %), walking (19.2 %) and touching (3.12 %). We found significant difference in the time spent between the daily activities (H = 41.67; p < 0.0001). Except activities involving touching, we found no significant seasonal differences in feeding, resting and walking activities by H. amphibius. Understanding the behavioral activities of H. amphibius will enhance management and conservation of the animals. The neurogenic fate of the hindbrain boundaries relies on Notch-dependent asymmetric cell divisions The generation of cell diversity in the central nervous system occurs during embryogenesis and requires a precise balance between cell proliferation, commitment to specific fates, and further neuronal differentiation. The cellular and molecular mechanisms regulating this balance in the embryonic brain are still poorly understood. Here we study how the neurogenic capacity in the embryonic hindbrain is spatiotemporally allocated, and how the fate and the growth of the hindbrain boundary cells are regulated. By generating a CRISPR-based knock-in zebrafish transgenic line to specifically label the hindbrain boundaries, we unveiled that boundary cells undergo a functional transition to become neurogenic during hindbrain segmentation concurrently as they maintain the progenitor cell pool. Boundary cells engaged in neurogenesis coinciding with the onset of Notch signaling, which triggered their asymmetrical cell division. Our findings reveal that distinct neurogenic phases take place during hindbrain growth and suggest that boundary cells contribute to refine the final number, identity, and proportion of neurons in the brain.

SUMMARYHindbrain boundary cells undergo a functional transition to become neurogenic concurrently as they are maintained as a progenitor cell pool. This involves a behavioral switch from symmetrically dividing progenitor cells to asymmetrically dividing progenitors, which depends on Notch-activity. Rho Kinase regulates neutrophil NET formation that is involved in UVB-induced skin inflammation ObjectiveUltraviolet B (UVB) is an important trigger of skin inflammation and lupus with leukocyte recruitment to inflamed skin. We recently reported the involvement of neutrophil NETosis in UVB-induced skin inflammation, and that NETotic nuclear envelope rupture is driven by PKC-mediated nuclear lamin B disassembly. To address the role of Actin cytoskeleton in NETosis, we investigated the effects of Rho kinase (ROCK) and its downstream actomyosin cytoskeletal networks on PKC nuclear translocation and NET formation, as well as their involvement in UVB-induced skin inflammation.

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

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

ConclusionsROCK regulated NETosis through modulation of PKC nuclear translocation via actomyosin cytoskeletal networks in neutrophils. ROCK1 deficiency ameliorated UVB- induced skin inflammation by attenuation of NETosis and NET-associated cytokines. Teosinte mexicana introgression modulates phosphatidylcholine levels and maize flowering time Native Americans domesticated maize (Zea mays ssp. mays) from lowland teosinte parviglumis (Zea mays ssp.parviglumis) in the warm Mexican southwest and brought it to the highlands of Mexico and South America where it was exposed to lower temperatures that imposed strong selection on flowering time. Phospholipids are important metabolites in plant responses to low-temperature and phosphorus availability, and have been suggested to influence flowering time. Here, we combined linkage mapping with genome scans to identify High PhosphatidylCholine 1 (HPC1), a gene that encodes a phospholipase A1 enzyme, as a major driver of phospholipid variation in highland maize. Common garden experiments demonstrated strong genotype-by-environment interactions associated with variation at HPC1, with the highland HPC1 allele leading to higher fitness in highlands, possibly by hastening flowering. The highland maize HPC1 variant resulted in impaired function of the encoded protein due to a polymorphism in a highly conserved sequence. A meta-analysis across HPC1 orthologs indicated a strong association between the identity of the amino acid at this position and optimal growth in prokaryotes. Mutagenesis of HPC1 via genome editing validated its role in regulating phospholipid metabolism. Finally, we showed that the highland HPC1 allele entered cultivated maize by introgression from the wild highland teosinte Zea mays ssp. mexicana and has been maintained in maize breeding lines from the Northern US, Canada and Europe. Thus, HPC1 introgressed from teosinte mexicana underlies a large metabolic QTL that modulates phosphatidylcholine levels and has an adaptive effect at least in part via induction of early flowering time. Distinct SARS-CoV-2 antibody reactivity patterns elicited by natural infection and mRNA Vaccination We analyzed data from two ongoing COVID-19 longitudinal serological surveys in Orange County, CA., between April 2020 and March 2021. A total of 8,476 finger stick blood specimens were collected before and after an aggressive mRNA vaccination campaign. IgG levels were determined using a multiplex antigen microarray containing 10 SARS-CoV-2 antigens, 4 SARS, 3 MERS, 12 Common CoV, and 8 Influenza antigens. Twenty-six percent of 3,347 specimens from unvaccinated Orange County residents in December 2020 were SARS-CoV-2 seropositive. The Ab response was predominantly against nucleocapsid (NP), full length spike and the spike S2 domain. Anti-receptor binding domain (RBD) reactivity was low and there was no cross-reactivity against SARS S1 or SARS RBD. An aggressive mRNA vaccination campaign at the UCI Medical Center started on December 16, 2020 and 6,724 healthcare workers were vaccinated within 3 weeks. Seroprevalence increased from 13% in December to 79% in January, 93% in February and 99% in March. mRNA vaccination induced much higher Ab levels especially against the RBD domain and significant cross-reactivity against SARS RBD and S1 was also observed. Nucleocapsid protein Abs can be used to distinguish individuals in a population of vaccinees to classify those who have been previously infected and those who have not, because nucleocapsid is not in the vaccine. Previously infected individuals developed higher Ab titers to the vaccine than those who have not been previously exposed. These results indicate that mRNA vaccination rapidly induces a much stronger and broader Ab response than SARS-CoV-2 infection. A multiscale lipid and cellular atlas of the human kidney The human kidney is composed of over 26 cell types that actively coordinate with each other to form higher-order structures, such as the nephron. It is not yet understood how these structures vary throughout a single organ or amongst the same organs within the human population. We have developed an extensive lipid and cellular atlas of the human kidney consisting of over 3 million cells comprising 75,000 functional tissue units (i.e., glomeruli, proximal tubules, distal tubules, and collecting ducts) from 13 human subjects. This atlas was developed using spatially registered and integrated technologies consisting of imaging mass spectrometry, multiplexed immunofluorescence, stained microscopy, and autofluorescence microscopy, to comprehensively probe large (i.e., centimeter-sized) areas of tissue. The cellular organization and lipid profiles of glomeruli, proximal tubules, distal tubules, and collecting ducts were discovered through these multimodal imaging data as well as their intra- and inter-subject variance. Relating the lipid profiles obtained from imaging mass spectrometry to distinct cell types obtained from immunofluorescence allowed us to hypothesize the functional role of specific phospholipids that have not previously been described. These hypotheses include subject characteristics, such as BMI and sex. The integrated data from the aforementioned datasets provide a valuable reference for kidney researchers, are publicly available through the NIH Human Biomolecular Atlas Program (https://portal.hubmapconsortium.org/), and discussed below. Neural reinstatement tracks attentional selection of object features in working memory Attention can be allocated in working memory (WM) to select and privilege relevant content. It is unclear whether attention selects individual features or whole objects in WM. Here, we used behavioural measures, eye-tracking and electroencephalography (EEG) to test the hypothesis that attention spreads between an objects features in WM. Twenty-six participants completed a WM task that asked them to recall the angle of one of two oriented, coloured bars after a delay while EEG and eye-tracking data was collected. During the delay, an orthogonal  incidental task cued the colour of one item for a match/mismatch judgement. On congruent trials (50%), the cued item was probed for subsequent orientation recall; on incongruent trials (50%), the other memory item was probed. As predicted, selecting the colour of an object in WM brought other features of the cued object into an attended state as revealed by EEG decoding, oscillatory -power, gaze bias and improved orientation recall performance. Together, the results show that attentional selection spreads between an objects features in WM, consistent with object-based attentional selection. Analyses of neural processing at recall revealed that the selected object was automatically compared with the probe, whether it was the target for recall or not. This provides a potential mechanism for the observed benefits of non-predictive cueing in WM, where a selected item is prioritised for subsequent decision-making. Missing the forest for the trees: Do seaweed ecosystems mitigate atmospheric CO2 emissions? Global seaweed carbon sequestration estimates are currently taken as the fraction of the net primary production (NPP) exported to the deep ocean. However, this perspective does not account for CO2 from the consumption of external subsidies. Here we clarify: i) the role of export relative to seaweed net ecosystem production (NEP) for a closed system and one more likely open to subsidies; ii) the importance of subsidies by compiling published estimates of NEP from seaweed-dominated ecosystems; and iii) discuss their impact on the global seaweed net carbon balance and other sequestration constraints as a mitigation service. Examples of seaweed NEP (n = 18) were sparse and variable. Nevertheless, the average NEP (-9.2mmol C m-2 day-1 SE {+/-} 11.6) suggested that seaweed ecosystems are a C source, becoming increasingly heterotrophic as their export is consumed. Critically, mitigation of greenhouse gas emissions was mixed relative to their replacement or baseline states, and where CO2 is supplied independently of organic metabolism and atmospheric exchange we caution a sole reliance on NEP or NPP. This will ensure a more accurate seaweed mitigation assessment, one that does exceed their capacity and is effective within a compliance and carbon trading scheme. 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. Platelet transcriptome yields progressive markers in chronic myeloproliferative neoplasms and identifies putative targets of therapy Predicting disease progression remains a particularly challenging endeavor in chronic degenerative disorders and cancer, thus limiting early detection, risk stratification, and preventive interventions. Here, profiling the spectrum of chronic myeloproliferative neoplasms (MPNs) as a model, we identify the blood platelet transcriptome as a proxy for highly sensitive progression biomarkers that also enables prediction of advanced disease via machine learning algorithms. Using RNA sequencing (RNA-seq), we derive disease-relevant gene expression in purified platelets from 120 peripheral blood samples constituting two time-separated cohorts of patients diagnosed with one of three MPN subtypes at sample acquisition - essential thrombocythemia, ET (n=24), polycythemia vera, PV (n=33), and primary or post ET/PV secondary myelofibrosis, MF (n=42), and healthy donors (n=21). The MPN platelet transcriptome reveals an incremental molecular reprogramming that is independent of patient driver mutation status or therapy and discriminates each clinical phenotype. Leveraging this dataset that shows a characteristic progressive expression gradient across MPN, we develop a machine learning model (Lasso-penalized regression) and predict advanced subtype MF at high accuracy and under two conditions of external validation: i) temporal: our two Stanford cohorts, AUC-ROC of 0.96; and ii) geographical: independently published data of an additional n=25 MF and n=46 healthy donors, AUC-ROC of 0.97). Lasso-derived signatures offer a robust core set of < 5 MPN transcriptome markers that are progressive in expression. Mechanistic insights from our data highlight impaired protein homeostasis as a prominent driver of MPN evolution, with persistent integrated stress response. We also identify JAK inhibitor-specific signatures and other interferon, proliferation, and proteostasis-associated markers as putative targets for MPN-directed therapy. Our platelet transcriptome snapshot of chronic MPNs demonstrates a proof of principle for disease risk stratification and progression beyond genetic data alone, with potential utility in other progressive disorders.

HighlightsLeveraging two independent and mutually validating MPN patient cohorts, we identify progressive transcriptomic markers that also enable externally validated prediction in MPNs.

Our platelet RNA-Seq data identifies impaired protein homeostasis as prominent in MPN progression and offers putative targets of therapy.

VISUAL ABSTRACT

O_FIG O_LINKSMALLFIG WIDTH=135 HEIGHT=200 SRC="FIGDIR/small/435190v3_ufig1.gif" ALT="Figure 1">
View larger version (42K):
org.highwire.dtl.DTLVardef@72dc16org.highwire.dtl.DTLVardef@cf5096org.highwire.dtl.DTLVardef@b3d460org.highwire.dtl.DTLVardef@3c0ddc_HPS_FORMAT_FIGEXP  M_FIG C_FIG Citation needed? Wikipedia and the COVID-19 pandemic BackgroundWith the COVID-19 pandemics outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an "infodemic", ensuring the quality of information is a crucial vector of public health. Investigating if and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked: which sources informed Wikipedias COVID-19-related articles before and during the pandemics first wave (January-May 2020).

ResultsWe found that coronavirus-related articles referenced trusted media sources and high-quality academic research. Moreover, despite a surge in COVID-19 preprints, Wikipedia had a clear preference for open-access studies published in respected journals and made little use of preprints. Building a timeline of English COVID-19 articles from 2001-2020 revealed a nuanced trade-off between quality and timeliness. It further showed how preexisting articles on key topics related to the virus created a framework for integrating new knowledge. Supported by a rigid sourcing policy, this "scientific infrastructure" facilitated contextualization and regulated the influx of new information. Lastly, we constructed a network of DOI-Wikipedia articles, which showed the shifting landscape of pandemic-related knowledge on Wikipedia and how academic citations create a web of shared knowledge supporting topics like COVID-19 vaccine development.

ConclusionsUnderstanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its "citizen encyclopedists", it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts. G protein-coupled estrogen receptor activation by Bisphenol-A disrupts protection from apoptosis conferred by estrogen receptors ERα and ERβ in pancreatic beta cells 17{beta}-estradiol protects pancreatic {beta}-cells from apoptosis via the estrogen receptors ER, ER{beta} and GPER. Conversely, the endocrine disruptor Bisphenol-A (BPA), which exerts multiple effects in this cell type via the same estrogen receptors, increased basal apoptosis. The molecular initiated events that trigger these opposite actions have yet to be identified. We demonstrated that combined genetic downregulation and pharmacological blockade of each estrogen receptor increased apoptosis to a different extent. The increase in apoptosis induced by BPA was diminished by the pharmacological blockade or the genetic silencing of GPER, and it was partially reproduced by the GPER agonist G1. BPA and G1-induced apoptosis were abolished upon pharmacological inhibition, silencing of ER and ER{beta}, or in dispersed islet cells from ER{beta} knockout (BERKO) mice. Yet, the ER and ER{beta} agonists, PPT and DPN, respectively, had no effect on beta cell viability. To exert their biological actions, ER and ER{beta} form homodimers and heterodimers. Molecular dynamic simulations together with proximity ligand assay and coimmunoprecipitation experiments indicated that the interaction of BPA with ER and ER{beta} as well as the GPER activation by G1 decreased ER{beta} heterodimers. We propose that ER{beta} heterodimers play an antiapoptotic role in beta cells and that BPA- and G1-induced decrease in ER{beta} heterodimers leads to beta cell apoptosis. Unveiling how different estrogenic chemicals affect the crosstalk among estrogen receptors should help to identify diabetogenic endocrine disruptors.

HighlightsO_LIPharmacological blockade and gene silencing of estrogen receptors ER, ER{beta} and GPER indicate that they are antiapoptotic in basal conditions.
C_LIO_LIGPER activation by G1 and BPA triggered apoptosis via a crosstalk with ER and ER{beta}.
C_LIO_LIBPA interaction with ER and ER{beta} as well as GPER activation decreased ER{beta} heterodimers, which was associated to increased apoptosis.
C_LIO_LIThis pathway represents a novel molecular initiating event underlying the pro-apoptotic effect of BPA
C_LIO_LIThe EndoC-{beta}H1 cell line may be a valid model of human {beta}-cells for identifying diabetogenic pollutants.
C_LI Hematopoietic differentiation is characterized by a transient peak of entropy at a single cell level. Hematopoietic differentiation has been metaphorically represented as linear trajectories with discrete steps from hematopoietic stem cells to mature cells. While the transcriptional state of cells at the beginning or at the end of these trajectories are well described from bulk analysis, what happens in the intermediate states has remained elusive until the use of single cell approaches. Applying Shannon entropy to measure cell-to-cell variability among cells at the same stage of differentiation, we observed a transient peak of gene expression variability in all the hematopoietic differentiation pathways. Strikingly, genes with the highest entropy variation in a given differentiation pathway matched genes known as pathway-specific, whereas genes with the highest expression variation were common to all pathways. Finally, we showed that the level of cell-to-cell variation is increased in the most immature compartment of hematopoiesis in myelodysplastic syndromes. These data suggest that differentiation could be better conceptualized as a dynamical stochastic process with a transient stage of cellular indetermination. Effects of substrate on shrimp growth, water quality and bacterial community in the biofloc system nursing Penaeus vannamei postlarvae This study aimed to investigate the effects of substrate on water quality, shrimp growth and bacterial community in the biofloc system with a salinity of 5{per thousand}. Two treatments, biofloc system with (sB) or without (nB) addition of elastic solid packing filler (nylon) as substrate, were set up. Penaeus vannamei postlarvae (PL, [~] stage 15) were stocked at a density of 4000 PL m-3 in each treatment with triplicates for a 28-days culture experiment, taking glucose as carbon source (C:N 15:1). Results showed that the survival rate (96.3{+/-}3.6%), FCR (0.76{+/-}0.06) and productivity (1.54{+/-}0.12 kg m-3) in sB treatment were significantly better than those in nB treatment (81.0{+/-}7.1%, 0.98{+/-}0.08 and 1.14{+/-}0.09 kg m-3, P<0.05). All water parameters were in the recommended ranges. Substrate showed significant effect on TAN, TSS, turbidity, biofloc volume, pH and carbonate alkalinity (P < 0.05). Actinobacteria (4.0-22.7%), Bacteroidetes (10.4-33.5%), Firmicutes (0.2-11.2%), Planctomycetes (4.0-14.9%) and Proteobacteria (29.4-59.0%) were the most dominant phyla for both treatments. However, the bacterial community in sB treatment showed to be significantly different from that in nB treatment (Jaccard distance 0.94{+/-}0.01, P=0.001). Substrate showed significant effects on Shannon, Heip, Pielou and Simpson index, as well as relative abundances of Actinobacteria, Bacteroidetes and Planctomycetes (P < 0.05). The results suggested that addition of substrate affected the shrimp growth, water quality and bacterial community in the biofloc system nursing P. vannamei PL with a 5{per thousand} salinity. 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. Multivariate Genomewide Association Analysis by Iterative Hard Thresholding 1In genome-wide association studies (GWAS), analyzing multiple correlated traits is potentially superior to conducting multiple univariate analyses. Standard methods for multivariate GWAS operate marker-by-marker and are computationally intensive. We present a penalized regression algorithm for multivariate GWAS based on iterative hard thresholding (IHT) and implement it in a convenient Julia package MendelIHT.jl (https://github.com/OpenMendel/MendelIHT.jl). In simulation studies with up to 100 traits, IHT exhibits similar true positive rates, smaller false positive rates, and faster execution times than GEMMAs linear mixed models and mv-PLINKs canonical correlation analysis. On UK Biobank data, our IHT software completed a 3-trait joint analysis in 20 hours and an 18-trait joint analysis in 53 hours, requiring up to 80GB of computer memory. In short, our software enables geneticists to fit a single regression model that simultaneously considers the effect of all SNPs and dozens of traits. Using Hierarchical Similarity To Examine The Genetics of Behcet's disease Behcets disease (BD) is a multisystem inflammatory disease that affects patients along the historic silk road. Thus far, the pathogenesis of the disease has proved elusive due to the complex genetic interactions and unknown environmental or viral triggering factors of the disease. In this paper, we seek to clarify the genetic factors of the disease while also uncovering other diseases of interest that present with a similar genotype as BD. To do this, we employ a convergent functional genomics approach by leveraging the hierarchical similarity tool available in Geneweaver. Through our analysis, we were able to ascertain 7 BD consensus genes and 16 autoimmune diseases with genetic overlap with BD. The results of our study will inform further research into the pathogenesis of Behcets Disease. Reduction of protein disulfide isomerase results in open conformations and stimulates dynamic exchange between structural ensembles Protein disulfide isomerase (PDI) is a ubiquitous redox-regulated enzyme that interacts with hundreds of client proteins intracellularly and extracellularly. It comprises two redox-sensitive domains, each hosting the conserved catalytic motif CxxC, two redox-insensitive protein-binding domains, and three linkers. Snapshots of oxidized and reduced PDI have been obtained by X-ray crystallography. Yet, how PDIs structure dynamically changes in response to the redox microenvironment and ligand binding remain unknown. Here, we used multiparameter confocal single-molecule Forster resonance energy transfer (smFRET) and multiple FRET pairs to track the movements of the two catalytic domains with high temporal resolution. Our studies document that, at equilibrium, PDI visits three structurally distinct conformational ensembles, two "open" (O1 and O2) and one "closed" (C). We show that the redox environment dictates the time spent in each ensemble and the rate at which they exchange. While oxidized PDI samples O1, O2 and C more evenly and in a slower fashion, reduced PDI predominantly populates O1 and O2, and exchanges between them more rapidly, on the sub-millisecond timescale. These findings were not expected based on crystallographic data. Using mutational analyses, we further demonstrate that the two active sites are structurally nonequivalent and that ligands targeting the active sites of reduced PDI shift the equilibrium towards closed conformations of the enzyme. This work introduces a new structural framework that challenges current views of PDI dynamics, helps rationalize the multifaced role of PDI in biology and may assist drug development. An estimate of the deepest branches of the tree of life from ancient vertically-evolving genes Core gene phylogenies provide a window into early evolution, but different gene sets and analytical methods have yielded substantially different views of the tree of life. Trees inferred from a small set of universal core genes have typically supported a long branch separating the archaeal and bacterial domains. By contrast, recent analyses of a broader set of non-ribosomal genes have suggested that Archaea may be less divergent from Bacteria, and that estimates of inter-domain distance are inflated due to accelerated evolution of ribosomal proteins along the inter-domain branch. Resolving this debate is key to determining the diversity of the archaeal and bacterial domains, the shape of the tree of life, and our understanding of the early course of cellular evolution. Here, we investigate the evolutionary history of the marker genes key to the debate. We show that estimates of a reduced Archaea-Bacteria (AB) branch length result from inter-domain gene transfers and hidden paralogy in the expanded marker gene set. By contrast, analysis of a broad range of manually curated marker gene datasets from an evenly sampled set of 700 Archaea and Bacteria reveal that current methods likely underestimate the AB branch length due to substitutional saturation and poor model fit; that the best-performing phylogenetic markers tend to support longer inter-domain branch lengths; and that the AB branch lengths of ribosomal and non-ribosomal marker genes are statistically indistinguishable. Furthermore, our phylogeny inferred from the 27 highest-ranked marker genes recovers a clade of DPANN at the base of the Archaea, and places CPR within Bacteria as the sister group to the Chloroflexota. 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. Newly developed ad hoc molecular assays show how eDNA can witness and anticipate the monk seal recolonization of central Mediterranean The monk seal Monachus monachus is the most endangered pinniped worldwide and the only one found in the Mediterranean, where its distribution and abundance have suffered a drastic decline in the last few decades. Data on its status are scattered due to both its rarity and evasiveness, and records are biased towards occasional, mostly coastal, encounters. Nowadays molecular techniques allow us to detect and quantify minute amounts of DNA traces released in the environment (eDNA) by any organism. We present three qPCR-assays targeting the monk seal mitogenome. The assays were soundly tested on an extensive and diversified sample set (n=73), including positive controls from Madeira breeding population collected during the peak of abundance, and two opportunistic Mediterranean eDNA-sample collections (offshore/coastal) from on-going projects. Monk seal DNA was detected in 47.2% and 66.7% of the samples collected in the Tyrrhenian from a ferry platform (2018-2019) and in the Pelagie archipelago -Strait of Sicily- (2020) respectively, anticipating (up to 2 year) visual observations occurred subsequently in proximity of the sampled areas. In the Tyrrhenian, detection occurrence increased between 2018 and 2019. Monk seal DNA recoveries were commoner in night-time ferry-samples, suggesting nocturnal predatory activity in pelagic waters. The proposed technique provides a non-invasive and yet highly-sensitive tool for defining the monk seal actual distribution and home range, its recovery rate and pinpoint coastal/offshore localities where prioritizing conservation, research, citizen science and education initiatives.