“Candidatus Competibacter”-lineage genomes retrieved from metagenomes reveal functional metabolic diversity

The glycogen-accumulating organism (GAO) ‘Candidatus Competibacter’ (Competibacter) uses aerobically stored glycogen to enable anaerobic carbon uptake, which is subsequently stored as polyhydroxyalkanoates (PHAs). This biphasic metabolism is key for the Competibacter to survive under the cyclic anaerobic-‘feast’: aerobic-‘famine’ regime of enhanced biological phosphorus removal (EBPR) wastewater treatment systems. As they do not contribute to phosphorus (P) removal, but compete for resources with the polyphosphate-accumulating organisms (PAO), thought responsible for P removal, their proliferation theoretically reduces the EBPR capacity. In this study, two complete genomes from Competibacter were obtained from laboratory-scale enrichment reactors through metagenomics. Phylogenetic analysis identified the two genomes, ‘Candidatus Competibacter denitrificans’ and ‘Candidatus Contendobacter odensis’, as being affiliated with Competibacter-lineage subgroups 1 and 5, respectively. Both have genes for glycogen and PHA cycling and for the metabolism of volatile fatty acids. Marked differences were found in their potential for the Embden–Meyerhof–Parnas and Entner–Doudoroff glycolytic pathways, as well as for denitrification, nitrogen fixation, fermentation, trehalose synthesis and utilisation of glucose and lactate. Genetic comparison of P metabolism pathways with sequenced PAOs revealed the absence of the Pit phosphate transporter in the Competibacter-lineage genomes—identifying a key metabolic difference with the PAO physiology. These genomes are the first from any GAO organism and provide new insights into the complex interaction and niche competition between PAOs and GAOs in EBPR systems

Accuracy of cause of death data routinely recorded in a population-based cancer registry: impact on cause-specific survival and validation using the Geneva Cancer Registry.

BACKGROUND: Information on the underlying cause of death of cancer patients is of interest because it can be used to estimate net survival. The population-based Geneva Cancer Registry is unique because registrars are able to review the official cause of death. This study aims to describe the difference between the official and revised cause-of-death variables and the impact on cancer survival estimates. METHODS: The recording process for each cause of death variable is summarised. We describe the differences between the two cause-of-death variables for the 5,065 deceased patients out of the 10,534 women diagnosed with breast cancer between 1970 and 2009. The Kappa statistic and logistic regression are applied to evaluate the degree of concordance. The impact of discordance on cause-specific survival is examined using the Kaplan Meier method. RESULTS: The overall agreement between the two variables was high. However, several subgroups presented a lower concordance, suggesting differences in calendar time and less attention given to older patients and more advanced diseases. Similarly, the impact of discordance on cause-specific survival was small on overall survival but larger for several subgroups. CONCLUSION: Estimation of cancer-specific survival could therefore be prone to bias when using the official cause of death. Breast cancer is not the more lethal cancer and our results can certainly not be generalised to more lethal tumours

Does true Gleason pattern 3 merit its cancer descriptor?

Nearly five decades following its conception, the Gleason grading system remains a cornerstone in the prognostication and management of patients with prostate cancer. In the past few years, a debate has been growing whether Gleason score 3 + 3 = 6 prostate cancer is a clinically significant disease. Clinical, molecular and genetic research is addressing the question whether well characterized Gleason score 3 + 3 = 6 disease has the ability to affect the morbidity and quality of life of an individual in whom it is diagnosed. The consequences of treatment of Gleason score 3 + 3 = 6 disease are considerable; few men get through their treatments without sustaining some harm. Further modification of the classification of prostate cancer and dropping the label cancer for Gleason score 3 + 3 = 6 disease might be warranted

Path segmentation for beginners: an overview of current methods for detecting changes in animal movement patterns

Increased availability of high-resolution movement data has led to the development of numerous methods for studying changes in animal movement behavior. Path segmentation methods provide basics for detecting movement changes and the behavioral mechanisms driving them. However, available path segmentation methods differ vastly with respect to underlying statistical assumptions and output produced. Consequently, it is currently difficult for researchers new to path segmentation to gain an overview of the different methods, and choose one that is appropriate for their data and research questions. Here, we provide an overview of different methods for segmenting movement paths according to potential changes in underlying behavior. To structure our overview, we outline three broad types of research questions that are commonly addressed through path segmentation: 1) the quantitative description of movement patterns, 2) the detection of significant change-points, and 3) the identification of underlying processes or ‘hidden states’. We discuss advantages and limitations of different approaches for addressing these research questions using path-level movement data, and present general guidelines for choosing methods based on data characteristics and questions. Our overview illustrates the large diversity of available path segmentation approaches, highlights the need for studies that compare the utility of different methods, and identifies opportunities for future developments in path-level data analysis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40462-016-0086-5) contains supplementary material, which is available to authorized users