Inflammasome priming in sterile inflammatory disease

The inflammasome is a cytoplasmic protein complex that processes interleukins (IL)-1β and IL-18, and drives a form of cell death known as pyroptosis. Oligomerization of this complex is actually the second step of activation, and a priming step must occur first. This involves transcriptional upregulation of pro-IL-1β, inflammasome sensor NLRP3, or the non-canonical inflammasome sensor caspase-11. An additional aspect of priming is the post-translational modification of particular inflammasome constituents. Priming is typically accomplished in vitro using a microbial Toll-like receptor (TLR) ligand. However, it is now clear that inflammasomes are activated during the progression of sterile inflammatory diseases such as atherosclerosis, metabolic disease, and neuroinflammatory disorders. Therefore, it is time to consider the endogenous factors and mechanisms that may prime the inflammasome in these conditions

The Nuclear Stellar Disk in Andromeda: A Fossil from the Era of Black Hole Growth

The physics of angular momentum transport from galactic scales (~10-100 pc) to much smaller radii is one of the oustanding problems in our understanding of the formation and evolution of super-massive black holes (BHs). Seemingly unrelated observations have discovered that there is a lopsided stellar disk of unknown origin orbiting the BH in M31, and possibly many other systems. We show that these nominally independent puzzles are in fact closely related. Multi-scale simulations of gas inflow from galactic to BH scales show that when sufficient gas is driven towards a BH, gravitational instabilities form a lopsided, eccentric disk that propagates inwards from larger radii. The lopsided stellar disk exerts a strong torque on the remaining gas, driving inflows that fuel the growth of the BH and produce quasar-level luminosities. The same disk can produce significant obscuration along many sightlines and thus may be the putative 'torus' invoked to explain obscured active galactic nuclei and the cosmic X-ray background. The stellar relic of this disk is long lived and retains the eccentric pattern. Simulations that yield quasar-level accretion rates produce relic stellar disks with kinematics, eccentric patterns, precession rates, and surface density profiles in reasonable agreement with observations of M31. The observed properties of nuclear stellar disks can thus be used to constrain the formation history of super-massive BHs.Comment: 6 pages, 4 figures, accepted to MNRAS Letters (matches published version

Expression in grasses of multiple transgenes for degradation of munitions compounds on live fire training ranges

The deposition of toxic munitions compounds, such as hexahydro-1, 3, 5-trinitro-1, 3, 5-triazine (RDX), on soils around targets in live-fire training ranges is an important source of groundwater contamination. Plants take up RDX but do not significantly degrade it. Reported here is the transformation of two perennial grass species, switchgrass (Panicum virgatum) and creeping bentgrass (Agrostis stolonifera), with the genes for degradation of RDX. These species possess a number of agronomic traits making them well equipped for the uptake and removal of RDX from root zone leachates. Transformation vectors were constructed with xplA and xplB, which confer the ability to degrade RDX, and nfsI, which encodes a nitroreductase for the detoxification of the co-contaminating explosive 2, 4, 6-trinitrotoluene (TNT). The vectors were transformed into the grass species using Agrobacterium tumefaciens infection. All transformed grass lines showing high transgene expression levels removed significantly more RDX from hydroponic solutions and retained significantly less RDX in their leaf tissues than wild-type plants. Soil columns planted with the best-performing switchgrass line were able to prevent leaching of RDX through a 0.5-m root zone. These plants represent a promising plant biotechnology to sustainably remove RDX from training range soil, thus preventing contamination of groundwater

The MSP-RON axis stimulates cancer cell growth in models of triple negative breast cancer

Triple negative breast cancer (TNBC) is the most aggressive subtype of breast cancer with poor prognosis and high rates of relapse. The lack of actionable targets for TNBC has contributed to the high mortality rates of this disease, and new candidate molecules for potential manipulation are urgently required. Here, we show that macrophage‐stimulating protein (MSP) and its tyrosine kinase receptor, RON, are potent drivers of cancer cell growth and tumor progression in a mouse model of TNBC driven by the loss of Trp53 and Brca1 . After comparison of two genetically engineered mouse models of TNBC, we found that mammary tumors from K14‐Cre;Brca1 F/F;Trp53 F/F (KB1P) mice exhibit high endogenous levels of MSP and RON expression. We show that MSP stimulates AKT and ERK1/2 activation as well as cancer cell growth in cell lines derived from the two mouse models, while genetic and pharmacological inhibition of RON prevents these effects. Similarly, KB1P tumor progression in mice was robustly attenuated by treatment with a RON inhibitor with accompanied reduction in the proliferation marker, Ki‐67. Analysis of human gene expression data confirmed that the genes encoding MSP and RON are robustly expressed in human TNBC as well as other subsets of breast cancer. Our findings uncover a mouse model where MSP and RON expression are naturally increased, and they provide evidence that this receptor and its ligand are viable candidate molecules for targeted treatment of breast cancer

International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci.

The risk of posttraumatic stress disorder (PTSD) following trauma is heritable, but robust common variants have yet to be identified. In a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls we conduct a genome-wide association study of PTSD. We demonstrate SNP-based heritability estimates of 5-20%, varying by sex. Three genome-wide significant loci are identified, 2 in European and 1 in African-ancestry analyses. Analyses stratified by sex implicate 3 additional loci in men. Along with other novel genes and non-coding RNAs, a Parkinson's disease gene involved in dopamine regulation, PARK2, is associated with PTSD. Finally, we demonstrate that polygenic risk for PTSD is significantly predictive of re-experiencing symptoms in the Million Veteran Program dataset, although specific loci did not replicate. These results demonstrate the role of genetic variation in the biology of risk for PTSD and highlight the necessity of conducting sex-stratified analyses and expanding GWAS beyond European ancestry populations

Cell-type-specific profiling of protein-DNA interactions without cell isolation using targeted DamID with next-generation sequencing.

This protocol is an extension to: Nat. Protoc. 2, 1467-1478 (2007); doi:10.1038/nprot.2007.148; published online 7 June 2007The ability to profile transcription and chromatin binding in a cell-type-specific manner is a powerful aid to understanding cell-fate specification and cellular function in multicellular organisms. We recently developed targeted DamID (TaDa) to enable genome-wide, cell-type-specific profiling of DNA- and chromatin-binding proteins in vivo without cell isolation. As a protocol extension, this article describes substantial modifications to an existing protocol, and it offers additional applications. TaDa builds upon DamID, a technique for detecting genome-wide DNA-binding profiles of proteins, by coupling it with the GAL4 system in Drosophila to enable both temporal and spatial resolution. TaDa ensures that Dam-fusion proteins are expressed at very low levels, thus avoiding toxicity and potential artifacts from overexpression. The modifications to the core DamID technique presented here also increase the speed of sample processing and throughput, and adapt the method to next-generation sequencing technology. TaDa is robust, reproducible and highly sensitive. Compared with other methods for cell-type-specific profiling, the technique requires no cell-sorting, cross-linking or antisera, and binding profiles can be generated from as few as 10,000 total induced cells. By profiling the genome-wide binding of RNA polymerase II (Pol II), TaDa can also identify transcribed genes in a cell-type-specific manner. Here we describe a detailed protocol for carrying out TaDa experiments and preparing the material for next-generation sequencing. Although we developed TaDa in Drosophila, it should be easily adapted to other organisms with an inducible expression system. Once transgenic animals are obtained, the entire experimental procedure-from collecting tissue samples to generating sequencing libraries-can be accomplished within 5 d.This work was funded by a Wellcome Trust Senior Investigator Award (103792), Wellcome Trust Programme Grant (092545) and BBSRC Project Grant (BB/L00786X/1) to A.H.B. A.H.B acknowledges core funding to the Gurdon Institute from the Wellcome Trust (092096) and CRUK (C6946/A14492).This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/nprot.2016.08

Capturing the cloud of diversity reveals complexity and heterogeneity of MRSA carriage, infection and transmission.

Genome sequencing is revolutionizing clinical microbiology and our understanding of infectious diseases. Previous studies have largely relied on the sequencing of a single isolate from each individual. However, it is not clear what degree of bacterial diversity exists within, and is transmitted between individuals. Understanding this 'cloud of diversity' is key to accurate identification of transmission pathways. Here, we report the deep sequencing of methicillin-resistant Staphylococcus aureus among staff and animal patients involved in a transmission network at a veterinary hospital. We demonstrate considerable within-host diversity and that within-host diversity may rise and fall over time. Isolates from invasive disease contained multiple mutations in the same genes, including inactivation of a global regulator of virulence and changes in phage copy number. This study highlights the need for sequencing of multiple isolates from individuals to gain an accurate picture of transmission networks and to further understand the basis of pathogenesis.Thanks to Dr Alex O’Neill, University of Leeds and Dr Matthew Ellington, Public Health England for provision of RN4220 and RN4200mutS. We thank the core sequencing and informatics team at the Wellcome Trust Sanger Institute for sequencing of the isolates described in this study. This work was supported by a Medical Research Council Partnership grant (G1001787/1) held between the Department of Veterinary Medicine, University of Cambridge (M.A.H.), the School of Clinical Medicine, University of Cambridge (S.J.P.), the Moredun Research Institute, and the Wellcome Trust Sanger Institute (J.P. and S.J.P). S.J.P. receives support from the NIHR Cambridge Biomedical Research Centre. M.T.G.H., S.R.H. and J.P. were funded by Wellcome Trust grant no. 098051. G.G.R.M. was funded by an MRC studentship.This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/ncomms756

ETS Transcription Factors Control Transcription of EZH2 and Epigenetic Silencing of the Tumor Suppressor Gene Nkx3.1 in Prostate Cancer

ETS transcription factors regulate important signaling pathways involved in cell differentiation and development in many tissues and have emerged as important players in prostate cancer. However, the biological impact of ETS factors in prostate tumorigenesis is still debated.We performed an analysis of the ETS gene family using microarray data and real-time PCR in normal and tumor tissues along with functional studies in normal and cancer cell lines to understand the impact in prostate tumorigenesis and identify key targets of these transcription factors. We found frequent dysregulation of ETS genes with oncogenic (i.e., ERG and ESE1) and tumor suppressor (i.e., ESE3) properties in prostate tumors compared to normal prostate. Tumor subgroups (i.e., ERG(high), ESE1(high), ESE3(low) and NoETS tumors) were identified on the basis of their ETS expression status and showed distinct transcriptional and biological features. ERG(high) and ESE3(low) tumors had the most robust gene signatures with both distinct and overlapping features. Integrating genomic data with functional studies in multiple cell lines, we demonstrated that ERG and ESE3 controlled in opposite direction transcription of the Polycomb Group protein EZH2, a key gene in development, differentiation, stem cell biology and tumorigenesis. We further demonstrated that the prostate-specific tumor suppressor gene Nkx3.1 was controlled by ERG and ESE3 both directly and through induction of EZH2.These findings provide new insights into the role of the ETS transcriptional network in prostate tumorigenesis and uncover previously unrecognized links between aberrant expression of ETS factors, deregulation of epigenetic effectors and silencing of tumor suppressor genes. The link between aberrant ETS activity and epigenetic gene silencing may be relevant for the clinical management of prostate cancer and design of new therapeutic strategies

Neuroimaging-Based Classification of PTSD Using Data-Driven Computational Approaches:A Multisite Big Data Study from the ENIGMA-PGC PTSD Consortium

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group.METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality.RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60% test AUC for s-MRI, 59% for rs-fMRI and 56% for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75% AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance.CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.</p