Characterisation of the bacterial and fungal communities associated with different lesion sizes of Dark Spot Syndrome occurring in the Coral Stephanocoenia intersepta

The number and prevalence of coral diseases/syndromes are increasing worldwide. Dark Spot Syndrome (DSS) afflicts numerous coral species and is widespread throughout the Caribbean, yet there are no known causal agents. In this study we aimed to characterise the microbial communities (bacteria and fungi) associated with DSS lesions affecting the coral Stephanocoenia intersepta using nonculture molecular techniques. Bacterial diversity of healthy tissues (H), those in advance of the lesion interface (apparently healthy AH), and three sizes of disease lesions (small, medium, and large) varied significantly (ANOSIM R = 0.052 p,0.001), apart from the medium and large lesions, which were similar in their community profile. Four bacteria fitted into the pattern expected from potential pathogens; namely absent from H, increasing in abundance within AH, and dominant in the lesions themselves. These included ribotypes related to Corynebacterium (KC190237), Acinetobacter (KC190251), Parvularculaceae (KC19027), and Oscillatoria (KC190271). Furthermore, two Vibrio species, a genus including many proposed coral pathogens, dominated the disease lesion and were absent from H and AH tissues, making them candidates as potential pathogens for DSS. In contrast, other members of bacteria from the same genus, such as V. harveyii were present throughout all sample types, supporting previous studies where potential coral pathogens exist in healthy tissues. Fungal diversity varied significantly as well, however the main difference between diseased and healthy tissues was the dominance of one ribotype, closely related to the plant pathogen, Rhytisma acerinum, a known causal agent of tar spot on tree leaves. As the corals’ symbiotic algae have been shown to turn to a darker pigmented state in DSS (giving rise to the syndromes name), the two most likely pathogens are R. acerinum and the bacterium Oscillatoria, which has been identified as the causal agent of the colouration in Black Band Disease, another widespread coral disease

Hemolymph microbiome of Pacific oysters in response to temperature, temperature stress and infection

Microbiota provide their hosts with a range of beneficial services, including defense from external pathogens. However, host-associated microbial communities themselves can act as a source of opportunistic pathogens depending on the environment. Marine poikilotherms and their microbiota are strongly influenced by temperature, but experimental studies exploring how temperature affects the interactions between both parties are rare. To assess the effects of temperature, temperature stress and infection on diversity, composition and dynamics of the hemolymph microbiota of Pacific oysters (Crassostrea gigas), we conducted an experiment in a fully-crossed, three-factorial design, in which the temperature acclimated oysters (8 or 22 °C) were exposed to temperature stress and to experimental challenge with a virulent Vibrio sp. Strain. We monitored oyster survival and repeatedly collected hemolymph of dead and alive animals to determine the microbiome composition by 16s rRNA gene amplicon pyrosequencing. We found that the microbial dynamics and composition of communities in healthy animals (including infection survivors) were significantly affected by temperature and temperature stress, but not by infection. The response was mediated by changes in the incidence and abundance of operational taxonomic units (OTUs) and accompanied by little change at higher taxonomic levels, indicating dynamic stability of the hemolymph microbiome. Dead and moribund oysters, on the contrary, displayed signs of community structure disruption, characterized by very low diversity and proliferation of few OTUs. We can therefore link short-term responses of host-associated microbial communities to abiotic and biotic factors and assess the potential feedback between microbiota dynamics and host survival during disease

Protein-Signaled Guided Bone Regeneration Using Titanium Mesh and Rh-BMP2 in Oral Surgery: A Case Report Involving Left Mandibular Reconstruction after Tumor Resection

Recombinant human bone morphogenetic protein-2 (rhBMP-2) is an osteoinductive protein approved for use in oral and maxillofacial defect reconstruction. Growth factors act as mediators of cellular growth on morphogenesis and mythogenesis phases. Utilized as recombinant proteins, these growth factors need the presence of local target cells capable of obtaining the required results. This cell population may be present at the wound site or added to scaffolding material before implantation at the surgical site

Projections of climate conditions that increase coral disease susceptibility and pathogen abundance and virulence

Rising sea temperatures are likely to increase the frequency of disease outbreaks affecting reef-building corals through impacts on coral hosts and pathogens. We present and compare climate model projections of temperature conditions that will increase coral susceptibility to disease, pathogen abundance and pathogen virulence. Both moderate (RCP 4.5) and fossil fuel aggressive (RCP 8.5) emissions scenarios are examined. We also compare projections for the onset of disease-conducive conditions and severe annual coral bleaching, and produce a disease risk summary that combines climate stress with stress caused by local human activities. There is great spatial variation in the projections, both among and within the major ocean basins, in conditions favouring disease development. Our results indicate that disease is as likely to cause coral mortality as bleaching in the coming decades. These projections identify priority locations to reduce stress caused by local human activities and test management interventions to reduce disease impacts

Moving toward a system genetics view of disease

Testing hundreds of thousands of DNA markers in human, mouse, and other species for association to complex traits like disease is now a reality. However, information on how variations in DNA impact complex physiologic processes flows through transcriptional and other molecular networks. In other words, DNA variations impact complex diseases through the perturbations they cause to transcriptional and other biological networks, and these molecular phenotypes are intermediate to clinically defined disease. Because it is also now possible to monitor transcript levels in a comprehensive fashion, integrating DNA variation, transcription, and phenotypic data has the potential to enhance identification of the associations between DNA variation and diseases like obesity and diabetes, as well as characterize those parts of the molecular networks that drive these diseases. Toward that end, we review methods for integrating expression quantitative trait loci (eQTLs), gene expression, and clinical data to infer causal relationships among gene expression traits and between expression and clinical traits. We further describe methods to integrate these data in a more comprehensive manner by constructing coexpression gene networks that leverage pairwise gene interaction data to represent more general relationships. To infer gene networks that capture causal information, we describe a Bayesian algorithm that further integrates eQTLs, expression, and clinical phenotype data to reconstruct whole-gene networks capable of representing causal relationships among genes and traits in the network. These emerging network approaches, aimed at processing high-dimensional biological data by integrating data from multiple sources, represent some of the first steps in statistical genetics to identify multiple genetic perturbations that alter the states of molecular networks and that in turn push systems into disease states. Evolving statistical procedures that operate on networks will be critical to extracting information related to complex phenotypes like disease, as research goes beyond a single-gene focus. The early successes achieved with the methods described herein suggest that these more integrative genomics approaches to dissecting disease traits will significantly enhance the identification of key drivers of disease beyond what could be achieved by genetic association studies alone

Reporting issues in group sequential randomised controlled trials: a systematic review protocol of published journal reports

Background: Adaptive designs are somewhat underused, despite prominence given to methodology in the statistical literature. Some concerns relates to robustness of adaptive designs in decision making, acceptability of trial findings to change practice, anxiety about early stopping of trials and worry about wrong decision making. These issues could be linked to inadequate reporting of the conduct of such clinical trials. We assess the reporting of group sequential randomised controlled trials (RCTs), which are one of the most well-understood adaptive designs in the confirmatory setting. Methods: We undertake a systematic review searching Ovid MEDLINE from 1st January 2001 to 23rd September 2014 and including parallel group confirmatory group sequential RCTs that were prospectively designed using the Frequentist approach. Eligible trials are screened for completeness in reporting against the CONSORT 2010 checklist with some proposed modifications to capture issues such as statistical bias correction following early stopping. Descriptive statistics aided with forest plots on CONSORT compliance are presented. Discussion: Reporting of the conduct of adaptive designs is an area which has not been fully explored. Hence, the findings from this study can enlighten us on the adequacy in reporting of well-understood group sequential RCTs as a class of adaptive designs and on ways to address some of the cited concerns. Most importantly, the study can inform policy makers on the adequacy of the current CONSORT statements in enhancing reporting of such adaptive designs