A metabolomics pipeline highlights microbial metabolism in bloodstream infections.

The growth of antimicrobial resistance (AMR) highlights an urgent need to identify bacterial pathogenic functions that may be targets for clinical intervention. Although severe infections profoundly alter host metabolism, prior studies have largely ignored microbial metabolism in this context. Here, we describe an iterative, comparative metabolomics pipeline to uncover microbial metabolic features in the complex setting of a host and apply it to investigate gram-negative bloodstream infection (BSI) in patients. We find elevated levels of bacterially derived acetylated polyamines during BSI and discover the enzyme responsible for their production (SpeG). Blocking SpeG activity reduces bacterial proliferation and slows pathogenesis. Reduction of SpeG activity also enhances bacterial membrane permeability and increases intracellular antibiotic accumulation, allowing us to overcome AMR in culture and in vivo. This study highlights how tools to study pathogen metabolism in the natural context of infection can reveal and prioritize therapeutic strategies for addressing challenging infections.

Nonparametric empirical Bayes biomarker imputation and estimation.

Biomarkers are often measured in bulk to diagnose patients, monitor patient conditions, and research novel drug pathways. The measurement of these biomarkers often suffers from detection limits that result in missing and untrustworthy measurements. Frequently, missing biomarkers are imputed so that down-stream analysis can be conducted with modern statistical methods that cannot normally handle data subject to informative censoring. This work develops an empirical Bayes g $$ g $$ -modeling method for imputing and denoising biomarker measurements. We establish superior estimation properties compared to popular methods in simulations and with real data, providing the useful biomarker measurement estimations for down-stream analysis.

Kernel Cox partially linear regression: Building predictive models for cancer patients' survival.

Wide heterogeneity exists in cancer patients' survival, ranging from a few months to several decades. To accurately predict clinical outcomes, it is vital to build an accurate predictive model that relates the patients' molecular profiles with the patients' survival. With complex relationships between survival and high-dimensional molecular predictors, it is challenging to conduct nonparametric modeling and irrelevant predictors removing simultaneously. In this article, we build a kernel Cox proportional hazards semi-parametric model and propose a novel regularized garrotized kernel machine (RegGKM) method to fit the model. We use the kernel machine method to describe the complex relationship between survival and predictors, while automatically removing irrelevant parametric and nonparametric predictors through a LASSO penalty. An efficient high-dimensional algorithm is developed for the proposed method. Comparison with other competing methods in simulation shows that the proposed method always has better predictive accuracy. We apply this method to analyze a multiple myeloma dataset and predict the patients' death burden based on their gene expressions. Our results can help classify patients into groups with different death risks, facilitating treatment for better clinical outcomes.

Association of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and gallstones among US adults aged ≤ 50 years: a cross-sectional study from NHANES 2017-2020.

BACKGROUND: The chronic digestive condition gallstones is quite common around the world, the development of which is closely related to oxidative stress, inflammatory response and abnormalities of lipid metabolism. In the last few years, as a novel biomarker of lipid metabolism, the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) has garnered significant interest. However, its relationship with gallstones has not been studied yet. METHODS: 3,772 people, all under 50, were included in this study, and their full data came from the National Health and Nutrition Examination Survey (NHANES) database for the years 2017-2020. Information on gallstones was obtained through self-reported questionnaires. Smoothed curve fitting multifactorial logistic regression was utilized to evaluate the connection of NHHR with gallstone formation incidence. Subsequently, subgroup analysis and interaction tests were applied. Finally, to create a prediction model, logistic regression and feature screening by last absolute shrinkage and selection operator (LASSO) were used. The resulting model was displayed using a nomogram. RESULTS: In multivariate logistic regression that accounted for all factors, there was a 77% increase in the likelihood of gallstones for every unit rise in lnNHHR (OR 1.77 [CI 1.11-2.83]). Following NHHR stratification, the Q4 NHHR level was substantially more linked to the risk of gallstones than the Q1 level (OR 1.86 [CI 1.04-3.32]). This correlation was stronger in women, people under 35, smokers, abstainers from alcohol, non-Hispanic White people, those with excessively high cholesterol, people with COPD, and people without diabetes. After feature screening, a predictive model and visualized nomogram for gallstones were constructed with an AUC of 0.785 (CI 0.745-0.819), which was assessed by DCA to be clinically important. CONCLUSION: In the group of people ≤ 50 years of age, elevated NHHR levels were substantially linked to a higher incidence of gallstones. This correlation was stronger in several specific groups such as females, under 35 years of age, smokers, and so on. Predictive models constructed using the NHHR have potential clinical value in assessing gallstone formation.

A homozygous missense mutation in the fibroblast growth factor 5 gene is associated with the long-hair trait in Angora rabbits.

BACKGROUND: Rabbits are well-domesticated animals. As a crucial economic animal, rabbit has been successfully bred into wool-use, meat-use and fur-use breeds. Hair length is one of the most economically important traits affecting profitability in wool rabbits. In this study, to identify selection signatures with the long-hair trait, whole-genomic resequencing of long-haired rabbits (Angora rabbits) and short-haired rabbits (Rex and New Zealand rabbits) was performed. RESULTS: By genome-wide selective sweeping analysis based on population comparison, we identified a total of 5.85 Mb regions (containing 174 candidate genes) with strong selection signals. Six of these genes (Dusp1, Ihh, Fam134a, Map3k1, Spata16, and Fgf5) were enriched in the MAPK signalling and Hedgehog signalling pathways, both of which are closely associated with hair growth regulation. Among these genes, Fgf5 encodes the FGF5 protein, which is a well-established regulator of hair growth. There was a nonsynonymous nucleotide substitution (T19234C) in the Fgf5 gene. At this locus, the C allele was present in all of the tested Angora rabbits, while the T allele was dominant in New Zealand and Rex rabbits. We further confirmed that the C allele was conserved in Angora rabbits by screening an additional 135 rabbits. Moreover, the results of functional predictions and co-immunoprecipitation revealed that the T19234C mutation impaired the binding capacity of FGF5 to its receptor FGFR1. CONCLUSIONS: We discovered that the homozygous missense mutation T19234C within Fgf5 might contribute to the long-hair trait of Angora rabbits by reducing its receptor binding capacity. This finding will provide new insights into the genetic basis underlying the genetic improvement of Angora rabbits and benefit the improvement of rabbit breeding in the future.

Mediator subunit MED1 deficiency prevents carbon tetrachloride-induced hepatic fibrosis in mice.

Mediator subunit mediator 1 (MED1) mediates ligand-dependent binding of the mediator coactivator complex to various nuclear receptors and plays a critical role in embryonic development, lipid and glucose metabolism, liver regeneration, and tumorigenesis. However, the precise role of MED1 in the development of liver fibrosis has been unclear. Here, we showed that MED1 expression was increased in livers from nonalcoholic steatohepatitis (NASH) patients and mice and positively correlated with transforming growth factor ß (TGF-ß) signaling and profibrotic factors. Upon treatment with carbon tetrachloride (CCl4), hepatic fibrosis was much less in liver-specific MED1 deletion (MED1ΔLiv) mice than in MED1fl/fl littermates. TGF-ß/Smad2/3 signaling pathway was inhibited, and gene expression of fibrotic markers, including α-smooth muscle actin (α-SMA), collagen type 1 α 1 (Col1a1), matrix metalloproteinase-2 (Mmp2), and metallopeptidase inhibitor 1 (Timp1) were decreased in livers of MED1ΔLiv mice with CCl4 injection. Transcriptomic analysis revealed that the differentially expressed genes in livers of CCl4-administered MED1ΔLiv mice were enriched in the pathway of oxidoreductase activity, followed by robustly reduced oxidoreductase activity-related genes, such as Gm4756, Txnrd3, and Etfbkmt. More importantly, we found that the reduction of reactive oxygen species (ROS) in MED1 knockdown hepatocytes blocked the activation of TGF-ß/Smad2/3 pathway and the expression of fibrotic genes in LX2 cells. These results indicate that MED1 is a positive regulator for hepatic fibrogenesis, and MED1 may be considered as a potential therapeutic target for the regression of liver fibrosis.NEW & NOTEWORTHY In this study, we present the first evidence that liver mediator 1 (MED1) deficiency attenuated carbon tetrachloride-induced hepatic fibrosis in mouse. The underlying mechanism is that MED1 deficiency reduces reactive oxygen species (ROS) production in hepatocytes, thus restricts the activation of TGF-ß/Smad2/3 signaling pathway and fibrogenic genes expression in hepatic stellate cells (HSCs). These data suggest that MED1 is an essential regulator for hepatic fibrogenesis, and MED1 may be considered as a potential therapeutic target for liver fibrosis.

MED1 Deficiency in Macrophages Aggravates Isoproterenol-Induced Cardiac Fibrosis in Mice.

Mediator 1 (MED1), a key subunit of the mediator complex, interacts with various nuclear receptors and functions in lipid metabolism and energy homeostasis. Dilated cardiomyopathy-related ventricular dilatation and heart failure have been reported in mice with cardiomyocyte-specific Med1 deficiency. However, the contribution of macrophage-specific MED1 in cardiac remodeling remains unclear. In this study, macrophage-specific Med1 knockout (Med1ΔMac) mice were generated and exposed to isoproterenol (ISO) to induce cardiac fibrosis; these mice showed aggravated cardiac fibrosis compared with Med1fl/fl mice. The levels of expression of marker genes for myofibroblast transdifferentiation [α-smooth muscle actin (SMA)] and of profibrotic genes, including Col1a1, Col3a1, Postn, Mmp2, Timp1, and Fn1, were significantly increased in the cardiac tissues of Med1ΔMac mice with ISO-induced myocardial fibrosis. In particular, the transforming growth factor (TGF)-ß-Smad2/3 signaling pathway was activated. In bone marrow-derived and peritoneal macrophages, Med1 deficiency was also associated with elevated levels of expression of proinflammatory genes, including Il6, Tnfa, and Il1b. These findings indicate that macrophage-specific MED1 deficiency may aggravate ISO-induced cardiac fibrosis via the regulation of the TGF-ß-SMAD2/3 pathway, and the underlying mechanism may involve MED1 deficiency triggering the activation of inflammatory cytokines in macrophages, which in turn may stimulate phenotypic switch of cardiac fibroblasts and accelerate cardiac fibrosis. Thus, MED1 is a potential therapeutic target for cardiac fibrosis.

A compound decision approach to covariance matrix estimation.

Covariance matrix estimation is a fundamental statistical task in many applications, but the sample covariance matrix is suboptimal when the sample size is comparable to or less than the number of features. Such high-dimensional settings are common in modern genomics, where covariance matrix estimation is frequently employed as a method for inferring gene networks. To achieve estimation accuracy in these settings, existing methods typically either assume that the population covariance matrix has some particular structure, for example, sparsity, or apply shrinkage to better estimate the population eigenvalues. In this paper, we study a new approach to estimating high-dimensional covariance matrices. We first frame covariance matrix estimation as a compound decision problem. This motivates defining a class of decision rules and using a nonparametric empirical Bayes g-modeling approach to estimate the optimal rule in the class. Simulation results and gene network inference in an RNA-seq experiment in mouse show that our approach is comparable to or can outperform a number of state-of-the-art proposals.

Genomic regions influencing aggressive behavior in honey bees are defined by colony allele frequencies.

For social animals, the genotypes of group members affect the social environment, and thus individual behavior, often indirectly. We used genome-wide association studies (GWAS) to determine the influence of individual vs. group genotypes on aggression in honey bees. Aggression in honey bees arises from the coordinated actions of colony members, primarily nonreproductive "soldier" bees, and thus, experiences evolutionary selection at the colony level. Here, we show that individual behavior is influenced by colony environment, which in turn, is shaped by allele frequency within colonies. Using a population with a range of aggression, we sequenced individual whole genomes and looked for genotype-behavior associations within colonies in a common environment. There were no significant correlations between individual aggression and specific alleles. By contrast, we found strong correlations between colony aggression and the frequencies of specific alleles within colonies, despite a small number of colonies. Associations at the colony level were highly significant and were very similar among both soldiers and foragers, but they covaried with one another. One strongly significant association peak, containing an ortholog of the Drosophila sensory gene dpr4 on linkage group (chromosome) 7, showed strong signals of both selection and admixture during the evolution of gentleness in a honey bee population. We thus found links between colony genetics and group behavior and also, molecular evidence for group-level selection, acting at the colony level. We conclude that group genetics dominates individual genetics in determining the fatal decision of honey bees to sting.

Urotensin II Enhances Advanced Aortic Atherosclerosis Formation and Delays Plaque Regression in Hyperlipidemic Rabbits.

Accumulated evidence shows that elevated urotensin II (UII) levels are associated with cardiovascular diseases. However, the role of UII in the initiation, progression, and regression of atherosclerosis remains to be verified. Different stages of atherosclerosis were induced in rabbits by a 0.3% high cholesterol diet (HCD) feeding, and either UII (5.4 µg/kg/h) or saline was chronically infused via osmotic mini-pumps. UII promoted atherosclerotic fatty streak formation in ovariectomized female rabbits (34% increase in gross lesion and 93% increase in microscopic lesion), and in male rabbits (39% increase in gross lesion). UII infusion significantly increased the plaque size of the carotid and subclavian arteries (69% increase over the control). In addition, UII infusion significantly enhanced the development of coronary lesions by increasing plaque size and lumen stenosis. Histopathological analysis revealed that aortic lesions in the UII group were characterized by increasing lesional macrophages, lipid deposition, and intra-plaque neovessel formation. UII infusion also significantly delayed the regression of atherosclerosis in rabbits by increasing the intra-plaque macrophage ratio. Furthermore, UII treatment led to a significant increase in NOX2 and HIF-1α/VEGF-A expression accompanied by increased reactive oxygen species levels in cultured macrophages. Tubule formation assays showed that UII exerted a pro-angiogenic effect in cultured endothelial cell lines and this effect was partly inhibited by urantide, a UII receptor antagonist. These findings suggest that UII can accelerate aortic and coronary plaque formation and enhance aortic plaque vulnerability, but delay the regression of atherosclerosis. The role of UII on angiogenesis in the lesion may be involved in complex plaque development.

Fat-1 expression alleviates atherosclerosis in transgenic rabbits.

Atherosclerosis is the main cause of cardiovascular diseases. The Fat-1 gene can express the n-3 fatty acid desaturase, which converts n-6 polyunsaturated fatty acids (PUFA) to n-3 PUFAs. The role of n-3 PUFAs in atherosclerosis is widely debated. This study explored the effect of n-3 PUFAs on atherosclerosis in rabbits. In this study, atherosclerosis was induced in Fat-1 transgenic rabbits and their littermate (WT) rabbits by feeding a high-cholesterol diet containing 0.3% cholesterol and 3% soybean oil for 16 weeks. Plasma lipid, fatty acid and pathological analyses of atherosclerotic lesions were conducted. Fatty acid composition in the liver and muscle showed that n-3 PUFAs increased and n-6 PUFAs decreased in the Fat-1 group. Plasma high-density lipoprotein cholesterol (HDL-C) levels were significantly increased in the Fat-1 group, and the atherosclerotic lesion area of the aortic arch in Fat-1 transgenic rabbits was significantly reduced. Histological analysis showed that smooth muscle cells (SMCs) in atherosclerotic lesions decreased significantly. In conclusion, n-3 PUFAs improve atherosclerosis in Fat-1 transgenic rabbits, and this process may depend on the increase in plasma HDL-C and the decrease in the amount of SMCs in atherosclerotic plaques.

TMT-based quantitative proteomic profiling of human monocyte-derived macrophages and foam cells.

BACKGROUND: Cardiovascular diseases remain the leading cause of morbidity and mortality worldwide, most of which are caused by atherosclerosis. Discerning processes that participate in macrophage-to-foam cell formation are critical for understanding the basic mechanisms underlying atherosclerosis. To explore the molecular mechanisms of foam cell formation, differentially expressed proteins were identified. METHODS: Human peripheral blood mononuclear cells were stimulated with macrophage colony-stimulating factor, and obtained macrophages were transformed into foam cells by oxidized low-density lipoprotein. Tandem mass tag (TMT) labeling combined with mass spectrometry was performed to find associations between foam cell transformation and proteome profiles. RESULTS: Totally, 5146 quantifiable proteins were identified, among which 1515 and 182 differentially expressed proteins (DEPs) were found in macrophage/monocyte and foam cell/macrophage, respectively. Subcellular localization analysis revealed that downregulated DEPs of macrophages/monocytes were mostly located in the nucleus, whereas upregulated DEPs of foam cells/macrophages were mostly extracellular or located in the plasma membrane. Functional analysis of DEPs demonstrated that cholesterol metabolism-related proteins were upregulated in foam cells, whereas immune response-related proteins were downregulated in foam cells. The protein interaction network showed that the DEPs with the highest interaction scores between macrophages and foam cells were mainly concentrated in lysosomes and the endoplasmic reticulum. CONCLUSIONS: Proteomics analysis suggested that cholesterol metabolism was upregulated, while the immune response was suppressed in foam cells. KEGG enrichment analysis and protein-protein interaction analysis indicated that DEPs located in the endoplasmic reticulum and lysosomes might be key drivers of foam cell formation. These data provide a basis for identifying the potential proteins associated with the molecular mechanism underlying macrophage transformation to foam cells.

Estimation of the proportion of treatment effect explained by a high-dimensional surrogate.

Clinical studies examining the effectiveness of a treatment with respect to some primary outcome often require long-term follow-up of patients and/or costly or burdensome measurements of the primary outcome of interest. Identifying a surrogate marker for the primary outcome of interest may allow one to evaluate a treatment effect with less follow-up time, less cost, or less burden. While much clinical and statistical work has focused on identifying and validating surrogate markers, available approaches tend to focus on settings in which only a single surrogate marker is of interest. Limited work has been done to accommodate the high-dimensional surrogate marker setting where the number of potential surrogates is greater than the sample size. In this article, we develop methods to estimate the proportion of treatment effect explained by high-dimensional surrogates. We study the asymptotic properties of our proposed estimator, propose inference procedures, and examine finite sample performance via a simulation study. We illustrate our proposed methods using data from a randomized study comparing a novel whey-based oral nutrition supplement with a standard supplement with respect to change in body fat percentage over 12 weeks, where the surrogate markers of interest are gene expression probesets.

Treatment with the Prolyl Hydroxylase Inhibitor JNJ Promotes Abdominal Aortic Aneurysm Progression in Diabetic Mice.

OBJECTIVE: Prolyl hydroxylase domain containing proteins (PHD) rigorously regulate intracellular hypoxia inducible factor-1 (HIF-1) protein expression and activity. Diabetes impairs PHD activity and attenuates abdominal aortic aneurysm (AAA) progression. The extent to which dysregulated PHD activity contributes to diabetes mediated AAA suppression remains undetermined. METHODS: AAAs were induced in diabetic and non-diabetic male C57BL/6J mice via intra-aortic elastase infusion. A PHD inhibitor (JNJ-42041935, aka "JNJ", 150 mmol/kg) or vehicle alone was administered daily starting one day prior to AAA induction for 14 days. Influences on AAA progression was assessed via ultrasonography and histopathology. Expression of aortic HIF-1α, three of its target genes and macrophage derived mediators were assayed via quantitative reverse transcription polymerase chain reaction. Aneurysmal sections from AAA patients with and without diabetes (two patients in each group) were immunostained for HIF-1α and vascular endothelial growth factor (VEGF)-A. RESULTS: Expression of HIF-1α target genes (erythropoietin, VEGF-A, and glucose transporter-1) was reduced by 45% - 95% in experimental diabetic aortas. Diameter enlargement was similarly limited, as were mural elastin degradation, leukocyte infiltration, and neo-angiogenesis (reduced capillary density and length) on histopathology. Pre-treatment with JNJ prior to AAA initiation augmented aortic HIF-1α target gene expression and aneurysm progression in diabetic mice, along with macrophage VEGF-A and matrix metalloproteinase 2 mRNA expression. No differences were noted in HIF-1α or VEGF-A expression on aortic immunohistochemical staining of human aortic tissue as a function of diabetes status. CONCLUSION: Small molecule PHD inhibitor treatment reduces or offsets impairment of experimental AAA progression in hyperglycemic mice, highlighting the potential contribution of dysregulated PHD activity to diabetes mediated aneurysm suppression.

Bayesian penalized Buckley-James method for high dimensional bivariate censored regression models.

For high dimensional gene expression data, one important goal is to identify a small number of genes that are associated with progression of the disease or survival of the patients. In this paper, we consider the problem of variable selection for multivariate survival data. We propose an estimation procedure for high dimensional accelerated failure time (AFT) models with bivariate censored data. The method extends the Buckley-James method by minimizing a penalized [Formula: see text] loss function with a penalty function induced from a bivariate spike-and-slab prior specification. In the proposed algorithm, censored observations are imputed using the Kaplan-Meier estimator, which avoids a parametric assumption on the error terms. Our empirical studies demonstrate that the proposed method provides better performance compared to the alternative procedures designed for univariate survival data regardless of whether the true events are correlated or not, and conceptualizes a formal way of handling bivariate survival data for AFT models. Findings from the analysis of a myeloma clinical trial using the proposed method are also presented.

Angiotensin-converting enzyme 2, coronavirus disease 2019, and abdominal aortic aneurysms.

OBJECTIVE: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the etiologic agent of the current, world-wide coronavirus disease 2019 (COVID-19) pandemic. Angiotensin-converting enzyme 2 (ACE2) is the SARS-CoV-2 host entry receptor for cellular inoculation and target organ injury. We reviewed ACE2 expression and the role of ACE2-angiotensin 1-7-Mas receptor axis activity in abdominal aortic aneurysm (AAA) pathogenesis to identify potential COVID-19 influences on AAA disease pathogenesis. METHODS: A comprehensive literature search was performed on PubMed, National Library of Medicine. Key words included COVID-19, SARS-CoV-2, AAA, ACE2, ACE or angiotensin II type 1 (AT1) receptor inhibitor, angiotensin 1-7, Mas receptor, age, gender, respiratory diseases, diabetes, and autoimmune diseases. Key publications on the epidemiology and pathogenesis of COVID-19 and AAAs were identified and reviewed. RESULTS: All vascular structural cells, including endothelial and smooth muscle cells, fibroblasts, and pericytes express ACE2. Cigarette smoking, diabetes, chronic obstructive pulmonary disease, lupus, certain types of malignancies, and viral infection promote ACE2 expression and activity, with the magnitude of response varying by sex and age. Genetic deficiency of AT1 receptor, or pharmacologic ACE or AT1 inhibition also increases ACE2 and its catalytic product angiotensin 1-7. Genetic ablation or pharmacologic inhibition of ACE2 or Mas receptor augments, whereas ACE2 activation or angiotensin 1-7 treatment attenuates, progression of experimental AAAs. The potential influences of SARS-CoV-2 on AAA pathogenesis include augmented ACE-angiotensin II-AT1 receptor activity resulting from decreased reciprocal ACE2-angiotensin 1-7-Mas activation; increased production of proaneurysmal mediators stimulated by viral spike proteins in ACE2-negative myeloid cells or by ACE2-expressing vascular structural cells; augmented local or systemic cross-talk between viral targeted nonvascular, nonleukocytic ACE2-expressing cells via ligand recognition of their cognate leukocyte receptors; and hypoxemia and increased systemic inflammatory tone experienced during severe COVID-19 illness. CONCLUSIONS: COVID-19 may theoretically influence AAA disease through multiple SARS-CoV-2-induced mechanisms. Further investigation and clinical follow-up will be necessary to determine whether and to what extent the COVID-19 pandemic will influence the prevalence, progression, and lethality of AAA disease in the coming decade.

miR-145 inhibits the proliferation and migration of vascular smooth muscle cells by regulating autophagy.

miR-145, the most abundant miRNA in the vascular smooth muscle cells (VSMCs), regulates VSMC function in intimal hyperplasia. It has been reported that autophagy participates in the regulation of proliferation and migration of VSMCs. However, the effect of miR-145 on autophagy and related mechanism in the proliferation and migration of VSMCs remains unclear. Therefore, we aimed to determine the effect of miR-145 on autophagy and the mechanism in VSMCs. Cell autophagy was determined by transmission electron microscope, mRFP-GFP-LC3 assay and Western blotting. A recombinant lentivirus containing miR-145 was used to construct VSMCs with miR-145 overexpression. We found that miR-145 expression was decreased, and autophagy was increased in the carotid arteries of C57BL/6J mice with intimal hyperplasia and TGF-ß1-stimulated VSMCs. Furthermore, miR-145 overexpression inhibited cell autophagy, whereas miR-145 inhibition promoted autophagy in TGF-ß1-stimulated VSMCs. Meanwhile, miR-145 inhibited the proliferation and migration of VSMCs. More importantly, our study showed that autophagy inhibition augmented the inhibitory effect of miR-145 on the proliferation and migration of VSMCs. In addition, we found that the sirtuins are not direct targets of miR-145 in the proliferation and migration of VSMCs. These results suggest that miR-145 inhibits the proliferation and migration of VSMCs by suppressing the activation of autophagy.

iMarmot: an integrative platform for comparative and functional genomics of marmots.

BACKGROUND: Marmots are large Holarctic rodents with unique biological features, making them potential animal models in various research fields. Due to the rapid accumulation of the genetic data in marmots, a highly integrative database is urgent needed. DESCRIPTION: iMarmot is freely available on the web at http://www.marmotdb.org/ and currently contains the biological information of 14 marmots, genomic sequence of 6 marmots, syntenic relationship and orthologs among 3 marmots, and expression profiles of several hibernators and plague hosts. To assist with the genomic and transcriptomic analysis, we also integrated a set of analysis and visualization tools, such as KEGG or GO enrichment analysis, PCA, Blast, Muscle, GeneWise, Lastz, and JBrowse. Particularly, one DEGs (differentially expressed genes) module has been implemented in this database to visualize the gene expression changes in hibernators and plague hosts. CONCLUSION: This database will provide comprehensive information and analysis platform for researchers interested in understanding the biological features of marmots.

Transcriptional regulatory dynamics drive coordinated metabolic and neural response to social challenge in mice.

Agonistic encounters are powerful effectors of future behavior, and the ability to learn from this type of social challenge is an essential adaptive trait. We recently identified a conserved transcriptional program defining the response to social challenge across animal species, highly enriched in transcription factor (TF), energy metabolism, and developmental signaling genes. To understand the trajectory of this program and to uncover the most important regulatory influences controlling this response, we integrated gene expression data with the chromatin landscape in the hypothalamus, frontal cortex, and amygdala of socially challenged mice over time. The expression data revealed a complex spatiotemporal patterning of events starting with neural signaling molecules in the frontal cortex and ending in the modulation of developmental factors in the amygdala and hypothalamus, underpinned by a systems-wide shift in expression of energy metabolism-related genes. The transcriptional signals were correlated with significant shifts in chromatin accessibility and a network of challenge-associated TFs. Among these, the conserved metabolic and developmental regulator ESRRA was highlighted for an especially early and important regulatory role. Cell-type deconvolution analysis attributed the differential metabolic and developmental signals in this social context primarily to oligodendrocytes and neurons, respectively, and we show that ESRRA is expressed in both cell types. Localizing ESRRA binding sites in cortical chromatin, we show that this nuclear receptor binds both differentially expressed energy-related and neurodevelopmental TF genes. These data link metabolic and neurodevelopmental signaling to social challenge, and identify key regulatory drivers of this process with unprecedented tissue and temporal resolution.

Genetic and molecular features for hepadnavirus and plague infections in the Himalayan marmot.

The Himalayan marmot (Marmota himalayana), a natural host and transmitter of plague, is also susceptible to the hepadnavirus infection. To reveal the genetic basis of the hepadnavirus susceptibility and the immune response to plague, we systematically characterized the features of immune genes in Himalayan marmot with those of human and mouse. We found that the entire major histocompatibility complex region and the hepatitis B virus pathway genes of the Himalayan marmot were conserved with those of humans. A Trim (tripartite motif) gene cluster involved in immune response and antiviral activity displays dynamic evolution, which is reflected by the duplication of Trim5 and the absence of Trim22 and Trim34. Three key regions of Ntcp, which is critical for hepatitis B virus entry, had high identity among seven species of Marmota. Moreover, we observed a severe alveolar hemorrhage, inflammatory infiltrate in the infected lungs and livers from Himalayan marmots after infection of EV76, a live attenuated Yersinia pestis strain. Lots of immune genes were remarkably up-regulated, which several hub genes Il2rγ, Tra29, and Nlrp7 are placed at the center of the gene network. These findings suggest that Himalayan marmot is a potential animal model for study on the hepadnavirus and plague infection.