An Immune Cell Atlas Reveals Dynamic COVID-19 Specific Neutrophil Programming Amenable to Dexamethasone Therapy SARS-CoV-2 is a novel coronavirus that causes acute respiratory distress syndrome (ARDS), death and long-term sequelae. Innate immune cells are critical for host defense but are also the primary drivers of ARDS. The relationships between innate cellular responses in ARDS resulting from COVID-19 compared to other causes of ARDS, such as bacterial sepsis is unclear. Moreover, the beneficial effects of dexamethasone therapy during severe COVID-19 remain speculative, but understanding the mechanistic effects could improve evidence-based therapeutic interventions. To interrogate these relationships, we developed an scRNA-Seq and plasma proteomics atlas (biernaskielab.ca/COVID_neutrophil). We discovered that compared to bacterial ARDS, COVID-19 was associated with distinct neutrophil polarization characterized by either interferon (IFN) or prostaglandin (PG) active states. Neutrophils from bacterial ARDS had higher expression of antibacterial molecules such as PLAC8 and CD83. Dexamethasone therapy in COVID patients rapidly altered the IFNactive state, downregulated interferon responsive genes, and activated IL1R2+ve neutrophils. Dexamethasone also induced the emergence of immature neutrophils expressing immunosuppressive molecules ARG1 and ANXA1, which were not present in healthy controls. Moreover, dexamethasone remodeled global cellular interactions by changing neutrophils from information receivers into information providers. Importantly, male patients had higher proportions of IFNactive neutrophils, a greater degree of steroid-induced immature neutrophil expansion, and increased mortality benefit compared to females in the dexamethasone era. Indeed, the highest proportion of IFNactive neutrophils was associated with mortality. These results define neutrophil states unique to COVID-19 when contextualized to other life-threatening infections, thereby enhancing the relevance of our findings at the bedside. Furthermore, the molecular benefits of dexamethasone therapy are also defined, and the identified pathways and plasma proteins can now be targeted to develop improved therapeutics.
Bioactive constituents of Verbena officinalis regulate killing efficiency of primary human natural killer cells by accelerating killing processes BackgroundNatural killer (NK) cells play a key role in eliminating tumorigenic and pathogen-infected cells. Verbena officinalis (V. officinalis) has been used as a medical plant in traditional and modern medicine, exhibiting anti-tumor and anti-inflammation activity, but its role in NK cells remains unclear.

PurposeThe impact of bioactive constituents of V. officinalis on immune responses remains largely elusive. In this work we investigated the potential targets of V. officinalis and focused on killing efficiency and related functions of NK cells regulated by bioactive constituents of V. officinalis.

Study design/methodsWe used primary human NK cells from peripheral blood mononuclear cells. Potential regulatory roles of selected compounds in NK killing function-related genes were first analyzed by network pharmacology approaches. Potential engagement between compounds and NK receptors was examined by molecular docking assay. Killing efficiency of NK cells was determined with real-time killing assay and live-cell imaging. Proliferation was examined by CFSE staining. Expression of cytotoxic proteins was analyzed using flow cytometry. Lytic granule release was quantified by CD107a degranulation assay. Contact time required for killing and determination of serial killers were analyzed using live cell imaging results.

ResultsResults from network pharmacology approaches and molecular docking analyses predicted that the five bioactive compounds (acteoside, apigenin, kaempferol, verbenalin and hastatoside) from V. officinalis can regulated various key genes essential for NK effector functions and can bind to NK inhibitory receptors as well as activating receptors, indicating their potential role in regulating NK killing capacity. Analyses of NK killing efficiency revealed that out of these five compounds verbenalin exhibited an encouraging potency to enhance NK killing efficiency. Further investigation showed that verbenalin did not affect proliferation, expression of cytotoxic proteins, or lytic granule degranulation, but rather reduced contact time required for killing, enhanced total killing events per NK cell, and elevated the fraction of killing competent NK cells.

ConclusionsIn this work, we have identified verbenalin as the most potent bioactive constituent from V. officinalis to enhance NK cell killing efficiency via accelerating killing processes and converting non-killers to killing competent NK cells without affecting the lytic granule pathway.
Brain-heart dynamics in emotional regulation under uncertainty indexes depressive risk Recent studies highlight interoception as essential to processing healthy emotion and to pathology of major depressive disorder (MDD). It has been reported that interoceptive responses are impaired in MDD and in healthy individuals with a high depressive risk (HDR). However, it is unclear how individual differences in HDR relate to neurophysiological underpinnings for interoceptive and emotional reactions under different degrees of certainty. We examined whether HDR mediates the relationship between a neurophysiological marker for interoception, heartbeat-evoked potential (HEP), and an index for cardiac reactivity, heart rate (HR) or heart rate variability (HRV). In a concurrent EEG-ECG experiment, 26 healthy participants underwent an emotion-evoking picture-evaluation task. Each of differential auditory cues was associated with certainty of the upcoming pleasant or unpleasant picture. The results showed attenuated HRV activity for certain cues in HDR individuals. Neural and physiological reactions to uncertain, unpleasant pictures were enhanced by depressive risk. These results suggest reduced responses in prediction processing and enlarged precision-weighted prediction error for unpleasant pictures. Finally, HDR significantly mediated the HEP and HR relationship for unexpected unpleasant stimuli. This study provides evidence that interoceptive predictive coding in the cardiac domain is altered by HDR and suggests that investigating brain-heart interactions related to predictive coding will offer insights into how to estimate depressive risk. Evaluation of critical data processing steps for reliable prediction of gene co-expression from large collections of RNA-seq data MotivationGene co-expression analysis is an attractive tool for leveraging enormous amounts of public RNA-seq datasets for the prediction of gene functions and regulatory mechanisms. However, the optimal data processing steps for the accurate prediction of gene co-expression from such large datasets remain unclear. Especially the importance of batch effect correction is understudied.

ResultsWe processed RNA-seq data of 68 human and 76 mouse cell types and tissues using 50 different workflows into 7,200 genome-wide gene co-expression networks. We then conducted a systematic analysis of the factors that result in high-quality co-expression predictions, focusing on normalization, batch effect correction, and measure of correlation. We confirmed the key importance of high sample counts for high-quality predictions. However, choosing a suitable normalization approach and applying batch effect correction can further improve the quality of co-expression estimates, equivalent to a >80% and >40% increase in samples. In larger datasets, batch effect removal was equivalent to a more than doubling of the sample size. Finally, Pearson correlation appears more suitable than Spearman correlation, except for smaller datasets.

ConclusionA key point for accurate prediction of gene co-expression is the collection of many samples. However, paying attention to data normalization, batch effects, and the measure of correlation can significantly improve the quality of co-expression estimates. Selective Src-Family B Kinase Inhibition Promotes Pulmonary Artery Endothelial Cell Dysfunction. Protein tyrosine kinases (PTKs) are essential for eukaryotic signaling. By targeting select PTKs, the group of drugs known as Tyrosine kinase inhibitors (TKIs) have proven to be effective for treating multiple diseases ranging from cancer to pulmonary fibrosis. However, some TKIs also paradoxically lead to the development of adverse conditions such as pulmonary arterial hypertension (PAH) by promoting endothelial cell dysfunction (ECD). We hypothesize that (1) subsets of PTKs may disproportionately modulate signaling pathways critical for endothelial homeostasis, such as BMPR2 signaling, and (2) inhibiting those pro-endothelial PTKs can promote the development of ECD. Herein we use an agnostic high-throughput siRNA screen to investigate how PTKs affect the canonical BMPR2 signaling pathway. Our major finding is that within the Src-family of non-receptor PTKs, the Src-B family promotes canonical BMPR2 signaling while the Src-A family suppresses it. We focus on two representative members of each family, Lck (for Src-B) and Fyn (for Src-A) that are the strongest activators or inhibitors of BMPR2 signaling in the screen. We confirm that Lck is expressed in the endothelium of pulmonary arteries and show that Lck knockout (termed si-Lck) in pulmonary artery endothelial cells (PAECs) suppresses canonical BMPR2 signaling while Fyn knockout (termed si-Fyn) promotes canonical BMPR2 signaling. Furthermore, Lck and Fyn are responsible for opposing functional behaviors in PAECs: si-Lck promotes apoptosis and interferes with tube formation while si-Fyn suppresses apoptosis and promotes tube formation. After analyzing the whole-transcriptome signature of si-Lck and si-Fyn PAECs we find that in addition to BMPR2 signaling suppression, si-Lck (and not si-Fyn) increases a broad number of ECD markers and increases canonical NF-{kappa}{beta} signaling. In summary, for the first time we show that Src-A and B Family of PTKs exert differential control over key endothelial cell signaling pathways resulting in direct phenotypic consequences. This knowledge may help to guide the design of more precise TKIs which avoid adverse drug reactions brought about through endothelial cell dysfunction. Sox8 remodels the cranial ectoderm to generate the ear The vertebrate inner ear arises from a pool of progenitors with the potential to contribute to all the sense organs and cranial ganglia in the head. Here we explore the molecular mechanisms that control ear specification from these precursors. Using a multi-omics approach combined with loss-of-function experiments we identify a core transcriptional circuit that imparts ear identity, along with the first genome-wide characterization of non-coding elements that integrate this information. This analysis places the transcription factor Sox8 at the top of the ear determination network. Introducing Sox8 into cranial ectoderm not only converts non-ear cells into ear progenitors, but also activates the cellular programs for ear morphogenesis and neurogenesis. Thus, Sox8 has the unique ability to remodel transcriptional networks in the cranial ectoderm towards ear identity. Non-invasive imaging of gene expression and protein secretion dynamics in living mice: identification of ectopic prothrombin expression as driver of thrombosis in cancer The topology of gene expression and protein localization is a crucial characteristic of life, where the spatiotemporal dynamic of secretory proteins instruct higher order organization, including the orchestration of developmental and adaptive programs. However tools to non-invasively interrogate the fate of secretory proteins in vivo are scarce. Here we introduce a genetic tagging strategy for in vivo imaging of the secretion and expression dynamics of secretory proteins in living animals. Applying this to a prototypical liver-derived secretory protein, we demonstrate that this approach, combined with optical in-vivo imaging, uncovers extrahepatic prothrombin expression in multiple novel anatomical sites (including testes, placenta, brain, kidney, heart and lymphatic system) and in emerging tumors, resulting in significant amounts of tumor-derived prothrombin in the blood with procoagulant properties. Syngeneic cell lines from this mouse model enable unravelling regulatory mechanisms in high resolution, and in a scalable format ex vivo. Beyond discovering new functions of proteins in a targeted manner, this model allows identifying rheostats in the cross-talk between gene expression and availability of a secretory protein. It is also a valuable resource for uncovering novel (tissue-specific) therapeutic vulnerabilities. Heterogeneity of circulating epithelial cells in breast cancer at single-cell resolution: identifying tumor and hybrid cells Circulating tumor cells and hybrid cells formed by the fusion of tumor cells with normal cells are leading players in metastasis and have prognostic relevance. Circulating tumor cells and hybrid cells are identified as CD45-negative and CD45-positive epithelial cells. However, such an approach is challenging because epithelial cells are observed in the blood of healthy individuals. In this study, we applied single-cell RNA sequencing to profile CD45-negative and CD45-positive circulating epithelial cells (CECs) in 20 breast cancer patients and one healthy donor. DNA ploidy analysis was used to identify the tumor and hybrid cells among CD45[boxh] and CD45+ CECs in patients, respectively. Functional enrichment analysis was applied to characterize aneuploid and diploid cells. Diploid cells were also annotated to generate cell-type candidates and analyzed for copy-number aberrations (CNAs) to confirm or refute their tumor origin. CD45[boxh] and CD45+ CECs were found in cancer patients (25.5 (range 0-404) and median 6.5 (0-147)) and the healthy donor (8 and 11 cells) and divided into three clusters. Two CD45[boxh] CEC clusters were predominantly aneuploid (97% and 98%), but one cluster contained more diploid (59%) than aneuploid cells. CD45+ CECs were mostly diploid: only clusters 1 and 2 had aneuploid cells (16% and 2%). Diploid CD45[boxh] and CD45+ CECs were annotated as different immune cells and surprisingly harbored many CNAs. Cancer-associated signaling pathways were found only in aneuploid cells of CD45[boxh] CEC cluster 1 and diploid cells of CD45+ CEC cluster 1. Thus, our findings suggest that CECs in breast cancer patients are a highly heterogeneous population comprising aneuploid (tumor and hybrid) and diploid (normal) cells. DNA ploidy analysis is an effective instrument for identifying tumor and hybrid cells among CD45[boxh] and CD45+ CECs, respectively. 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. Phenotypic Heterogeneity Facilitates Survival While Hindering the Evolution of Drug Resistance Due to Intraspecific Competition Rising rates of resistance to antimicrobial drugs threatens the effective treatment of infections across the globe. Drug resistance has been established to emerge from non-genetic mechanisms, such as "persistence" in quiescent microbes and fluctuations in gene expression in actively replicating cells, as well as from genetic mutations. However, it is still unclear how non-genetic drug resistance affects the evolution of genetic drug resistance. We develop deterministic and stochastic population models that incorporate resource competition to quantitatively investigate the transition from non-genetic to genetic resistance during the exposure to static and cidal drugs. We find that non-genetic resistance facilitates the survival of cell populations during drug treatment, but that it hinders the development of genetic resistance due to the competition between the non-genetically and genetically resistant subpopulations. Non-genetic drug resistance in the presence of subpopulation competition is found to increase the first-appearance and fixation times of drug resistance mutations, while increasing the probability of mutation before population extinction during cidal drug treatment. Intense intraspecific competition during drug treatment leads to extinction of the susceptible and non-genetically resistant subpopulations. These findings advance our fundamental understanding of the evolution of drug resistance and may guide novel treatment strategies for patients with drug-resistant infections.

SIGNIFICANCEDrug resistance is predicted to kill as many as 10 million people per year and cost over 100 trillion USD in cumulative lost production globally by 2050. To mitigate these socio-economic costs, we need to fundamentally understand the drug resistance process. We investigate the effect that different forms of resistance have on the evolution of drug resistance using mathematical modeling and computer simulations. We find that the presence of non-genetically drug-resistant cells (whose resistance is temporary and not encoded in a genetic mutation) allows the population to survive drug treatment, while competition between these subpopoulations simultaneously slows down the evolution of permanent genetic drug resistance and in some cases drives them extinct. These findings have important implications for advancing evolutionary theory and for developing effective "resistance-proof" treatments. A Eukaryotic Circuit for Secrete-and-Sense Autonomy Cancers represent complex autonomous robust systems, displaying interconnectivity with feedback control. Autonomous growth is fueled by a cancer cells ability to  secrete-and-sense growth factors: a poorly understood phenomenon. Using an integrated systems and experimental approach, here we dissect the impact of a feedback-coupled GTPase circuit within the secretory pathway that imparts secretion-coupled autonomy. The circuit is assembled when the Ras-superfamily monomeric GTPase Arf1, and the heterotrimeric GTPase Giabg and their corresponding GAPs and GEFs are coupled by GIV/Girdin, a protein that is known to fuel aggressive traits in diverse cancers. One forward and two key negative feedback loops within the circuit create closed-loop control (CLC), allow the two GTPases to coregulate each other, and convert the expected switch-like behavior of Arf1-dependent secretion into an unexpected dose response alignment behavior of sensing and secretion. Such behavior translates into cell survival that is self-sustained by stimuli-proportionate secretion. Findings highlight how enhanced coupling of two biological switches in cancer cells is critical for multiscale feedback control to achieve secretion-coupled autonomy.

GRAPHIC ABSTRACT

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org.highwire.dtl.DTLVardef@183ff5corg.highwire.dtl.DTLVardef@f21de7org.highwire.dtl.DTLVardef@1893683org.highwire.dtl.DTLVardef@159d966_HPS_FORMAT_FIGEXP  M_FIG C_FIG In BriefThis work delivers an experimentally validated dynamical systems model of the cooperativity between two distinct classes of biological switches in eukaryotic cells and reveals the basis of secretion-coupled cellular autonomy in cancer.

HIGHLIGHTSO_LIModeling and experimental approaches were used to dissect a coupled GTPase circuit
C_LIO_LICoupling enables closed loop feedback and mutual control of GTPases
C_LIO_LICoupling generates dose response alignment behavior of sensing and secretion.
C_LIO_LICoupling is critical for multiscale feedback control to achieve secretion-coupled autonomy.
C_LI Maternal microbiota Bifidobacterium promotes placental morphogenesis, nutrient transport and fetal growth in mice The gut microbiota plays a central role in regulating host metabolism. However, while substantial progress has been made in discerning how the microbiota influences host functions post birth and beyond, little is known about how key members of the maternal gut microbiota can influence feto-placental growth. Here, using germ-free and specific-pathogen-free mice, we demonstrate that the bacterium Bifidobacterium breve UCC2003 modulates maternal body adaptations, placental structure and nutrient transporter capacity, with implications for fetal metabolism and growth. The effects of B. breve UCC2003 on feto-placental growth are mediated, in part, by changes in the maternal and placental metabolome (i.e. acetate and carnitine). Histological analysis of the placenta confirmed that Bifidobacterium modifies placental structure via changes in Igf2P0, Dlk1, Mapk1 and Mapk14 expression. Additionally, B. breve UCC2003, acting through Slc2a1 and Fatp1-4 transporters, was shown to restore fetal glycaemia and fetal growth in association with changes in the fetal hepatic transcriptome. This study provides knowledge towards a novel and safe therapeutic strategy for treating pregnancy disorders via modulation of the maternal gut microbiota. ABPP-HT* - Deep meets fast for activity-based profiling of deubiquitylating enzymes using advanced DIA mass spectrometry methods Activity-based protein profiling (ABPP) uses a combination of activity-based chemical probes with mass spectrometry (MS) to selectively characterise a particular enzyme or enzyme class. ABPP has proven invaluable for profiling enzymatic inhibitors in drug discovery. When applied to cell extracts and cells, challenging the ABP-enzyme complex formation with a small molecule can simultaneously inform on potency, selectivity, reversibility/binding affinity, permeability, and stability. ABPP can also be applied to pharmacodynamic studies to inform on cellular target engagement within specific organs when applied to in vivo models. Recently, we established separate high depth and high throughput ABPP (ABPP-HT) protocols for the profiling of deubiquitylating enzymes (DUBs). However, the combination of the two, deep and fast, in one method has been elusive. To further increase the sensitivity of the current ABPP-HT workflow we implemented state-of-the-art data-independent acquisition (DIA) and data-dependent acquisition (DDA) MS analysis tools. Hereby, we describe an improved methodology, ABPP-HT* (enhanced high-throughput-compatible activity-based protein profiling), that in combination with DIA MS methods allowed for the consistent profiling of 35-40 DUBs and provided a reduced number of missing values, whilst maintaining a throughput of 100 samples per day. The impact of housing conditions on mesenchymal stromal/stem cell populations differ between adipose tissue and skeletal muscle BackgroundIn pigs, the ratio between lean mass and fat mass in the carcass determines production efficiency and is strongly influenced by the number and size of cells in tissues. During growth, the increase in the number of cells results from the recruitment of different populations of multipotent mesenchymal stromal/stem cells (MSCs) residing in the tissues. We hypothesized that the impact of hygiene of housing conditions during growth on the proportions of MSCs in adipose tissue and skeletal muscle may differ between pigs with different residual feed intake (RFI), a measure of feed efficiency.

MethodsAt the age of 12 weeks, Large White pigs from two lines divergently selected for low and high RFI were housed in two contrasting hygiene conditions (good vs poor). After six weeks, pigs were slaughtered (n = 30; 5-9/group). Samples of subcutaneous adipose tissue and longissimus skeletal muscle were collected, and cells from the stromal vascular fraction (SVF), which includes mesenchymal stromal/stem cell populations, were isolated from each tissue. Adipose and muscle cell populations from the SVF were phenotyped by flow cytometry using antibodies that targeted different cell surface markers (CD45 to separate hematopoietic cells from MSCs; CD34, CD38, CD56 and CD140a to identify MSC populations with adipogenic and/or myogenic potential).

ResultsAdipose tissue and muscle shared some common MSC populations although MSC diversity was higher in muscle than in adipose tissue. In muscle, the CD45-CD56+CD34-CD140a+ and CD45-CD56+CD34+CD140a+ cell populations were abundant. Of these two cell populations, only the proportions of CD45-CD56+CD34+CD140a+ cells increased (P < 0.05) in pigs housed in poor hygiene as compared with pigs in good hygiene conditions. For the CD45-CD56-CD34- cell population, present in low proportion, there was an interaction between hygiene condition and genetic line (P < 0.05) with a decrease in low RFI pigs housed in poor hygiene conditions. In adipose tissue, the two abundant MSC populations were CD45-CD56-CD34- and CD45-CD56+CD34-. The proportion of CD45-CD56-CD34- cells increased (P < 0.05) whereas the proportion of CD45-CD56+CD34- tended to decrease (P < 0.1) in pigs housed in poor conditions. This study shows that the proportions of some MSC populations were affected by hygiene of housing conditions in a tissue-dependent manner in pigs of both RFI lines. It suggests that MSCs may play a significant role in adipose tissue and skeletal muscle homeostasis and may influence later growth and body composition in growing animals. Systematic monitoring of photosynthetically-derived oxidative signals by a peroxiredoxin-based biosensor Transmission of reductive cues from the photosynthetic electron transport chain to redox-regulated proteins plays a crucial role in activating chloroplast metabolism. However, deciphering the role of their counterbalanced oxidative signals is challenging due to monitoring difficulties. Here, we demonstrate the light-depended redox modification of chloroplast-targeted 2-Cys peroxiredoxins and introduce peroxiredoxin-based biosensors to monitor photosynthetically-derived oxidative signals. By employing a set of genetically encoded biosensors, we show the induction of oxidative signals under habitual light intensities and their inverse relationship with NADPH levels, unraveling the combined activity of reducing and oxidizing signals in fine-tuning chloroplast metabolism. A faster increase in carbon assimilation rates during photosynthesis induction phase was measured in plants deficient in 2-Cys peroxiredoxins compared to wild-type, suggesting the involvement of oxidative signals in attenuating photosynthesis under variable light environments. We suggest that oxidative signals measured by peroxiredoxin-based biosensors reflect the limitation to photosynthesis imposed by the redox regulatory system.

One-Sentence SummaryA genetically encoded biosensor unmasked the dominant role of photosynthetically-derived oxidative signals under habitual conditions. Ultrahigh-Throughput Ambient MS: Direct Analysis at 22 Samples per Second by Infrared Matrix-Assisted Desorption Electrospray Ionization Mass Spectrometry Infrared Matrix-Assisted Laser Desorption Electrospray Ionization (IR-MALDESI) mass spectrometry is an ambient-direct sampling method being developed for high-throughput, label-free, biochemical screening of large-scale compound libraries. Here, we report the development of an ultrahigh-throughput continuous motion IR-MALDESI sampling approach capable of acquiring data at rates up to 22.7 samples per second in a 384-well microtiter plate. At top speed, less than 1% analyte carryover is observed from well-to-well and signal intensity relative standard deviations (RSD) of 11.5% and 20.9% for 3 M 1-hydroxymidazolam and 12 M dextrorphan, respectively, are achieved. The ability to perform parallel kinetics studies on 384 samples with ~30s time resolution using an isocitrate dehydrogenase 1 (IDH1) enzyme assay is shown. Finally, we demonstrate the repeatability and throughput of our approach by measuring 115,200 samples from 300 microtiter plate reads consecutively over 5.54 hours with RSDs under 8.14% for each freshly introduced plate. Taken together, these results demonstrate the use of IR-MALDESI at sample acquisition rates that surpass other currently reported direct sampling mass spectrometry approaches used for high throughput compound screening.

For Table of Contents Only

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org.highwire.dtl.DTLVardef@5f916corg.highwire.dtl.DTLVardef@4473b4org.highwire.dtl.DTLVardef@82e8forg.highwire.dtl.DTLVardef@128b57b_HPS_FORMAT_FIGEXP  M_FIG C_FIG IRGM/Irgm1 Aggravates Progression of Atherosclerosis by Inducing Macrophage Apoptosis through the MAPK Signaling Pathway AimsAtherosclerosis underlies most cardiovascular diseases, among which acute coronary syndrome (ACS) caused by plaque rupture (PR) often leads to death. Immune-related GTPases (IRGM/Irgm1) have been extensively studied in inflammatory diseases, but their role in atherosclerosis is unclear. Determining how IRGM/Irgm1 promotes atherosclerotic plaque vulnerability will provide information for new biomarkers and/or therapeutic targets.

Methods and resultsWe identified ruptured and unruptured plaques by optical coherence tomography, and found that serum IRGM was highly expressed in patients with ST-segment elevation myocardial infarction in PR. We used ApoE-/-Irgm1+/+, ApoE-/-Irgm1+/- mice and chimeric mice to establish a model of advanced atherosclerosis. The results of pathological experiments showed that Irgm1 caused plaque necrosis. The ratio of neutral lipids and cholesterol crystals increases, while the content of collagen fibers decreases, aggravating the destabilization of atherosclerotic plaques. In vitro, we used multiple approaches to confirm that Irgm1 promotes macrophage apoptosis by promoting the production of reactive oxygen species and activating the MAPK signaling pathway.

ConclusionsIRGM may be a potential risk factor for PR. Mechanistic studies have shown that IRGM/Irgm1 contributes to the formation and rupture of fragile plaques. This is partly mediated by the induction of macrophage apoptosis via the MAPK signaling pathway. IRGM may offer new strategies for early treatment of ACS.

Translation viewOur findings indicate that IRGM/Irgm1 contributes to formation and rupture of vulnerable plaques. It suggests that IRGM may provide a new target for the early treatment of ACS. The spatial configuration of biotic interactions shapes coexistence-area relation-ships in an annual plant community The increase of species richness with area is a universal phenomenon on Earth. How-ever, this observation contrasts with our poor understanding of how these species-area relationships (SARs) emerge from the collective effects of area, spatial heterogeneity, and local interactions. By combining a structuralist approach with five years of empirical observations in a highly-diverse Mediterranean grassland, we show that spatial hetero-geneity plays a little role in the accumulation of species richness with area in our system. Instead, as we increase the sampled area more species combinations are realized, and they coexist mainly due to direct pairwise interactions rather than by changes in single-species dominance or by indirect interactions. We also identify a small set of transient species with small population sizes that are consistently found across spatial scales. These findings empirically support the importance of the architecture of species interactions together with stochastic events for driving coexistence- and species-area relationships. Deciphering the potential niche of two novel black yeast fungi from a biological soil crust based on their genomes, phenotypes, and melanin regulation Black yeasts are polyextremotolerant fungi that contain high amounts of melanin in their cell wall and maintain a primarily yeast form. These fungi grow in xeric, nutrient deplete environments which implies that they require highly flexible metabolisms and the ability to form lichen-like mutualisms with nearby algae and bacteria. However, the exact ecological niche and interactions between these fungi and their surrounding community is not well understood. We have isolated two novel black yeast fungi of the genus Exophiala: E. viscosium and E. limosus, which are from dryland biological soil crusts. A combination of whole genome sequencing and various phenotyping experiments have been performed on these isolates to determine their fundamental niches within the biological soil crust consortium. Our results reveal that these Exophiala spp. are capable of utilizing a wide variety of carbon and nitrogen sources potentially from symbiotic microbes, they can withstand many abiotic stresses, and can potentially provide UV resistance to the crust community in the form of secreted melanin. Besides the identification of two novel species within the genus Exophiala, our study also provides new insight into the production and regulation of melanin in extremotolerant fungi. First detection of herpesvirus and prevalence 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. Improving GWAS discovery and genomic prediction accuracy in Biobank data Genetically informed and deep-phenotyped biobanks are an important research resource. The cost of phenotyping far outstrips that of genotyping, and therefore it is imperative that the most powerful, versatile and efficient analysis approaches are used. Here, we apply our recently developed Bayesian grouped mixture of regressions model (GMRM) in the UK and Estonian Biobanks and obtain the highest genomic prediction accuracy reported to date across 21 heritable traits. On average, GMRM accuracies were 15% (SE 7%) greater than prediction models run in the LDAK software with SNP annotation marker groups, 18% (SE 3%) greater than a baseline BayesR model without SNP markers grouped into MAF-LD-annotation categories, and 106% (SE 9%) greater than polygenic risk scores calculated from mixed-linear model association (MLMA) estimates. For height, the prediction accuracy R2 was 47% in a UK Biobank hold-out sample, which was 76% of the estimated [Formula]. We then extend our GMRM prediction model to provide MLMA SNP marker estimates for GWAS discovery, which increased the independent loci detected to 7,910 in unrelated UK Biobank individuals, as compared to 5,521 from BoltLMM and 5,727 from Regenie, a 43% and 38% increase respectively. The average{chi} 2 value of the leading markers was 34% (SE 5.11) higher for GMRM as compared to Regenie, and increased by 17% for every 1% increase in prediction accuracy gained over a baseline BayesR model across the traits. Thus, we show that modelling genetic associations accounting for MAF and LD differences among SNP markers, and incorporating prior knowledge of genomic function, is important for both genomic prediction and for discovery in large-scale individual-level biobank-scale studies. Preprints in motion: tracking changes between preprint posting and journal publication during a pandemic Amidst the COVID-19 pandemic, preprints in the biomedical sciences are being posted and accessed at unprecedented rates, drawing widespread attention from the general public, press and policymakers for the first time. This phenomenon has sharpened longstanding questions about the reliability of information shared prior to journal peer review. Does the information shared in preprints typically withstand the scrutiny of peer review, or are conclusions likely to change in the version of record? We assessed preprints from bioRxiv and medRxiv that had been posted and subsequently published in a journal through 30th April 2020, representing the initial phase of the pandemic response. We utilised a combination of automatic and manual annotations to quantify how an article changed between the preprinted and published version. We found that the total number of figure panels and tables changed little between preprint and published articles. Moreover, the conclusions of 7.2% of non-COVID-19-related and 17.2% of COVID-19-related abstracts undergo a discrete change by the time of publication, but the majority of these changes do not qualitatively change the conclusions of the paper. Once-daily feeding is associated with better health in companion dogs: Results from the Dog Aging Project A variety of diets have been studied for possible anti-aging effects. In particular, studies of intermittent fasting and time-restricted feeding in laboratory rodents have found evidence of beneficial health outcomes. Companion dogs represent a unique opportunity to study diet in a large mammal that shares human environments. The Dog Aging Project has been collecting data on thousands of companion dogs of all different ages, sizes, and breeds since 2019. We leveraged this diverse cross-sectional dataset to investigate associations between feeding frequency and cognitive function (n = 10,474) as well as nine broad categories of health conditions (n = 24,238). Controlling for sex, age, breed, and other potential confounders, we found that dogs fed once daily rather than more frequently had lower mean scores on a cognitive dysfunction scale, and lower odds of having gastrointestinal, dental, orthopedic, kidney/urinary, and liver/pancreas disorders. Therefore, we find that once-daily feeding is associated with better health in multiple domains. Future research with longitudinal data can provide stronger evidence for a possible causal effect of feeding frequency on health in companion dogs. A Hierarchy of Biomolecular Proportional-Integral-Derivative Feedback Controllers for Robust Perfect Adaptation and Dynamic Performance Proportional-Integral-Derivative (PID) feedback controllers have been the most widely used controllers in industry for almost a century due to their good performance, simplicity, and ease of tuning. Motivated by their success in various engineering disciplines, PID controllers recently found their way into synthetic biology, where the design of feedback molecular control systems has been identified as an important goal. In this paper, we consider the mathematical realization of PID controllers via biomolecular interactions. We propose an array of topologies that offer a compromise between simplicity and high performance. We first demonstrate that different Proportional-Integral (PI) controllers exhibit different capabilities for enhancing the dynamics and reducing variance (cell-to-cell variability). Next, we introduce several derivative controllers that are realized based on incoherent feedforward loops acting in a feedback configuration. Alternatively, we show that differentiators can be realized by placing molecular integrators in a negative feedback loop--an arrangement that can then be augmented by PI components to yield PID feedback controllers. We demonstrate that the derivative component can be exploited for enhancing system stability, dramatically increasing the molecular control systems dynamic performance, and for reducing the noise effect on the output of interest. The PID controller features are established through various deterministic and stochastic analyses as well as numerical simulations. Finally, we provide an experimental demonstration using a recently developed hybrid setup, the cyberloop, where the controller is implemented in silico to control a biological genetic circuit in vivo. The large array of novel biomolecular PID controllers introduced here forms a basis for the design and construction of advanced high-performance biomolecular control systems that robustly regulate the dynamics of living systems. Trade-offs between cost of ingestion and rate of intake drive defensive toxin use Animals that ingest toxins can become unpalatable and even toxic to predators and parasites through toxin sequestration. Because most animals rapidly eliminate toxins to survive their ingestion, it is unclear how populations transition from susceptibility and toxin elimination to tolerance and accumulation as chemical defense emerges. Studies of chemical defense have generally focused on species with active toxin sequestration and target-site insensitivity mutations or toxin-binding proteins that permit survival without necessitating toxin elimination. Here, we investigate whether animals that presumably rely on toxin elimination for survival can utilize ingested toxins for defense. We use the A4 and A3 Drosophila melanogaster fly strains from the Drosophila Synthetic Population Resource (DSPR), which respectively possess elevated and reduced metabolic nicotine resistance amongst DSPR fly lines. We find that ingesting nicotine increased A4 but not A3 fly survival against Leptopilina heterotoma wasp parasitism.Further, we find that despite possessing genetic variants that enhance toxin elimination, A4 flies accrued more nicotine than A3 individuals likely by consuming more media. Our results suggest that enhanced toxin metabolism can allow for greater toxin intake by offsetting the cost of toxin ingestion. Passive toxin accumulation that accompanies increased toxin intake may underlie the early origins of chemical defense. IRI-CCE: A Platform for Evaluating CRISPR-based Base Editing Tools and Its Components Rapid assessment of CRISPR/Cas (Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR associated Cas protein)-based genome editing (GE) tools and their components are critical aspects for successful applications in different organisms. In many bacteria, double-stranded breaks (DSBs) generated by CRISPR/Cas tool generally cause cell death due to the lack of an efficient non-homologous end-joining pathway and restricts its use. CRISPR-based DSB-free base editors (BEs) have been applied for precise nucleotide editing in bacteria, which does not need to make DSBs. However, optimization of newer BE tools in bacteria is challenging owing to the toxic effects of BE reagents expressed using strong promoters. Improved variants of two main BEs capable of converting C-to-T (CBE) and A-to-G (ABE) have been recently developed but yet to be tested in bacteria. Here, we report a platform for in vivo rapid investigation of CRISPR-BE components in Escherichia coli (IRI-CCE) comprising different combinations of promoters/terminators. We demonstrate the use of IRI-CEE to characterize different variants of CBEs (PmCDA1, evoCDA1, APOBEC3A) and ABEs (ABE8e, ABE9e), exhibiting that each independent BE has its specific editing pattern for a given target site and promoter type. Additionally, the IRI-CCE platform offers a rapid way to screen functional gRNAs. In summary, CRISPR-BE components expressed by promoters of different strengths in the IRI-CCE allow an analysis of various BE tools, including cloned biopart modules and gRNAs.