Sensitivity and specificity of a nested polymerase chain reaction for detection of lentivirus infection in lions (Panthera leo)

Feline immunodeficiency virus (FIV) is a lentivirus in the Retroviridae family that causes lifelong infection in domestic cats. The lentivirus of African lions (Panthera leo), referred to as FIVple, is endemic in certain lion populations in eastern and southern Africa. Lentivirus infection leads to immunologic dysfunction and immunosuppressive disease in domestic cats; however, little is known about the pathogenic effects of infection in lions, nor about the epidemiologic impact on free-ranging and captive populations. Whole blood and serum samples were collected opportunistically from free-ranging lions in Kruger National Park, Republic of South Africa (RSA). Whole blood and serum samples were also collected from captive wild lions in the RSA. A nested polymerase chain reaction (PCR) assay for detection of FIV was performed on all whole blood samples. In addition, serum samples were tested for cross-reactive antibodies to domestic feline lentivirus antigens and puma lentivirus synthetic envelope peptide antigen. The PCR assay successfully amplified the lion lentivirus from African lions. The relative sensitivity and relative specificity were 79% and 100%, respectively, and the positive and negative predictive values were 100% and 67%, respectively. This research represents the first study to compare genetic material with antibody-based methods of lentivirus detection on lions in RSA. Using PCR as an additional diagnostic test for FIV in lions will increase screening sensitivity and will allow viral characterization among circulating isolates and monitoring of changes in the viral epidemiology within geographic regions and populations over time

The discovery of a z=0.7092 OH megamaser with the MIGHTEE survey

We present the discovery of the most distant OH megamaser to be observed in the main lines, using data from the MeerKAT International Giga-Hertz Tiered Extragalactic Exploration (MIGHTEE) survey. At a newly measured redshift of $z = 0.7092$, the system has strong emission in both the 1665MHz ($L \approx 2500$ L$_{\odot}$) and 1667 MHz ($L \approx 4.5\times10^4$ L$_{\odot}$) transitions, with both narrow and broad components. We interpret the broad line as a high-velocity-dispersion component of the 1667 MHz transition, with velocity $v \sim 330$km s$^{-1}$ with respect to the systemic velocity. The host galaxy has a stellar mass of $M_{\star} = 2.95 \times 10^{10}$ M$_{\odot}$ and a star-formation rate of SFR = 371 M$_{\odot}$yr$^{-1}$, placing it $\sim 1.5$dex above the main sequence for star-forming galaxies at this redshift, and can be classified as an ultra-luminous infrared galaxy. Alongside the optical imaging data, which exhibits evidence for a tidal tail, this suggests that the OH megamaser arises from a system that is currently undergoing a merger, which is stimulating star formation and providing the necessary conditions for pumping the OH molecule to saturation. The OHM is likely to be lensed, with a magnification factor of $\sim 2.5$, and perhaps more if the maser emitting region is compact and suitably offset relative to the centroid of its host galaxy's optical light. This discovery demonstrates that spectral line mapping with the new generation of radio interferometers may provide important information on the cosmic merger history of galaxies.Comment: 11 pages, accepted for publication in MNRA

Modern supratidal microbialites fed by groundwater: functional drivers, value and trajectories

Microbial mats were the dominant habitat type in shallow marine environments between the Palaeoarchean and Phanerozoic. Many of these (termed ‘microbialites’) calcified as they grew but such lithified mats are rare along modern coasts for reasons such as unsuitable water chemistry, destructive metazoan influences and competition with other reef-builders such as corals or macroalgae. Nonetheless, extant microbialites occur in unique coastal ecosystems such as the Exuma Cays, Bahamas or Lake Clifton and Hamelin Pool, Australia, where limitations such as calcium carbonate availability or destructive bioturbation are diminished. Along the coast of South Africa, extensive distributions of living microbialites (including layered stromatolites) have been discovered and described since the early 2000s. Unlike the Bahamian and Australian ecosystems, the South African microbialites form exclusively in the supratidal coastal zone at the convergence of emergent groundwater seepage. Similar systems were documented subsequently in southwestern Australia, Northern Ireland and the Scottish Hebrides, as recently as 2018, revealing that supratidal microbialites have a global distribution. This review uses the best-studied formations to contextualise formative drivers and processes of these supratidal ecosystems and highlight their geological, ecological and societal relevance

Integration of copy number and transcriptomics provides risk stratification in prostate cancer : a discovery and validation cohort study

Study data are deposited in NCBI GEO (unique identifier number GSE70770).Background : Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. Methods : In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone. Findings : We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer ( MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions. Interpretation : For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.Publisher PDFPeer reviewe

Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study.

BACKGROUND: Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. METHODS: In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone. FINDINGS: We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions. INTERPRETATION: For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.Cambridge work was funded by a CRUK programme grant awarded to DEN; Swedish work and tissue collections were funded by grants from the Linne Centre for Breast and Prostate Cancer (CRISP, grant 70867901), Karolinska Institutet, the Swedish Research Council (K2010-70X-20430-04-3), and the Swedish Cancer Society (11-0287).This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ebiom.2015.07.01

Structure and catalytic regulatory function of ubiquitin specific protease 11 N-terminal and ubiquitin-like domains

The ubiquitin specific protease 11 (USP11) is implicated in DNA repair, viral RNA replication, and TGFβ signaling. We report the first characterization of the USP11 domain architecture and its role in regulating the enzymatic activity. USP11 consists of an N-terminal "domain present in USPs" (DUSP) and "ubiquitin-like" (UBL) domain, together referred to as DU domains, and the catalytic domain harboring a second UBL domain. Crystal structures of the DU domains show a tandem arrangement with a shortened β-hairpin at the two-domain interface and altered surface characteristics compared to the homologues USP4 and USP15. A conserved VEVY motif is a signature feature at the two-domain interface that shapes a potential protein interaction site. Small angle X-ray scattering and gel filtration experiments are consistent with the USP11DU domains and full-length USP11 being monomeric. Unexpectedly, we reveal, through kinetic assays of a series of deletion mutants, that the catalytic activity of USP11 is not regulated through intramolecular autoinhibition or activation by the N-terminal DU or UBL domains. Moreover, ubiquitin chain cleavage assays with all eight linkages reveal a preference for Lys(63)-, Lys(6)-, Lys(33)-, and Lys(11)-linked chains over Lys(27)-, Lys(29)-, and Lys(48)-linked and linear chains consistent with USP11's function in DNA repair pathways that is mediated by the protease domain. Our data support a model whereby USP11 domains outside the catalytic core domain serve as protein interaction or trafficking modules rather than a direct regulatory function of the proteolytic activity. This highlights the diversity of USPs in substrate recognition and regulation of ubiquitin deconjugation

The discovery of a z = 0.7092 OH megamaser with the MIGHTEE survey

DATA AVAILABILITY : The MeerKAT visibility data for the MIGHTEE project are available from the SARAO archive under proposal IDs SCI-20180516-KH-01 and SCI-20180516-KH-02. A public release of the reduced image and catalogue products for the first MIGHTEE spectral line data release covering the COSMOS field is imminent (Heywood et al., in preparation).Please read abstract in the article.The Science and Technology Facilities Council (STFC); a United Kingdom Research and Innovation (UKRI) Frontiers Research Grant; the South African Radio Astronomy Observatory which is a facility of the National Research Foundation (NRF), an agency of the Department of Science and Innovation (DSI); the South African Research Chairs Initiative of the DSI/NRF; the National Science Foundation; the Radcliffe Institute for Advanced Study at Harvard University; the Instituto Nazionale Di Astrofisica (INAF); the Inter-University Institute for Data Intensive Astronomy (IDIA), a partnership of the University of Cape Town, the University of Pretoria, and the University of the Western Cape; the South African Department of Science and Innovation’s National Research Foundation.https://academic.oup.com/mnrashj2024PhysicsNon

The discovery of a z = 0.7092 OH megamaser with the MIGHTEE survey

We present the discovery of the most distant OH megamaser (OHM) to be observed in the main lines, using data from the MeerKAT International Giga-Hertz Tiered Extragalactic Exploration (MIGHTEE) survey. At a newly measured redshift of z = 0.7092, the system has strong emission in both the 1665 MHz (L ≈ 2500 L⊙) and 1667 MHz (L ≈ 4.5 × 104 L⊙) transitions, with both narrow and broad components. We interpret the broad line as a high-velocity-dispersion component of the 1667 MHz transition, with velocity v ∼ 330 km s−1 with respect to the systemic velocity. The host galaxy has a stellar mass of M⋆ = 2.95 × 1010 M⊙ and a star formation rate of SFR = 371 M⊙ yr−1, placing it ∼1.5 dex above the main sequence for star-forming galaxies at this redshift, and can be classified as an ultraluminous infrared galaxy. Alongside the optical imaging data, which exhibit evidence for a tidal tail, this suggests that the OHM arises from a system that is currently undergoing a merger, which is stimulating star formation and providing the necessary conditions for pumping the OH molecule to saturation. The OHM is likely to be lensed, with a magnification factor of ∼2.5, and perhaps more if the maser emitting region is compact and suitably offset relative to the centroid of its host galaxy’s optical light. This discovery demonstrates that spectral line mapping with the new generation of radio interferometers may provide important information on the cosmic merger history of galaxies

DESNT: A Poor Prognosis Category of Human Prostate Cancer.

BACKGROUND: A critical problem in the clinical management of prostate cancer is that it is highly heterogeneous. Accurate prediction of individual cancer behaviour is therefore not achievable at the time of diagnosis leading to substantial overtreatment. It remains an enigma that, in contrast to breast cancer, unsupervised analyses of global expression profiles have not currently defined robust categories of prostate cancer with distinct clinical outcomes. OBJECTIVE: To devise a novel classification framework for human prostate cancer based on unsupervised mathematical approaches. DESIGN, SETTING, AND PARTICIPANTS: Our analyses are based on the hypothesis that previous attempts to classify prostate cancer have been unsuccessful because individual samples of prostate cancer frequently have heterogeneous compositions. To address this issue, we applied an unsupervised Bayesian procedure called Latent Process Decomposition to four independent prostate cancer transcriptome datasets obtained using samples from prostatectomy patients and containing between 78 and 182 participants. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Biochemical failure was assessed using log-rank analysis and Cox regression analysis. RESULTS AND LIMITATIONS: Application of Latent Process Decomposition identified a common process in all four independent datasets examined. Cancers assigned to this process (designated DESNT cancers) are characterized by low expression of a core set of 45 genes, many encoding proteins involved in the cytoskeleton machinery, ion transport, and cell adhesion. For the three datasets with linked prostate-specific antigen failure data following prostatectomy, patients with DESNT cancer exhibited poor outcome relative to other patients (p=2.65×10-5, p=4.28×10-5, and p=2.98×10-8). When these three datasets were combined the independent predictive value of DESNT membership was p=1.61×10-7 compared with p=1.00×10-5 for Gleason sum. A limitation of the study is that only prediction of prostate-specific antigen failure was examined. CONCLUSIONS: Our results demonstrate the existence of a novel poor prognosis category of human prostate cancer and will assist in the targeting of therapy, helping avoid treatment-associated morbidity in men with indolent disease. PATIENT SUMMARY: Prostate cancer, unlike breast cancer, does not have a robust classification framework. We propose that this failure has occurred because prostate cancer samples selected for analysis frequently have heterozygous compositions (individual samples are made up of many different parts that each have different characteristics). Applying a mathematical approach that can overcome this problem we identify a novel poor prognosis category of human prostate cancer called DESNT.This work was funded by the Bob Champion Cancer Trust, The Masonic Charitable Foundation successor to The Grand Charity, The King Family, and The University of East Anglia. We acknowledge support from Movember, from Prostate Cancer UK, Callum Barton, and from The Andy Ripley Memorial Fund. The research presented in this paper was carried out on the High Performance Computing Cluster supported by the Research and Specialist Computing Support service at the University of East Anglia. Cancer Research UK Grant 10047 funded the generation of the prostate CancerMap expression microarray dataset. We would like to acknowledge the support of the National Institute for Health Research which funds the Cambridge Bio-medical Research Centre, Cambridge UK