Macroecology in the age of Big Data – Where to go from here?

Recent years have seen an exponential increase in the amount of data available in all sciences and application domains. Macroecology is part of this “Big Data” trend, with a strong rise in the volume of data that we are using for our research. Here, we summarize the most recent developments in macroecology in the age of Big Data that were presented at the 2018 annual meeting of the Specialist Group Macroecology of the Ecological Society of Germany, Austria and Switzerland (GfÖ). Supported by computational advances, macroecology has been a rapidly developing field over recent years. Our meeting highlighted important avenues for further progress in terms of standardized data collection, data integration, method development and process integration. In particular, we focus on (a) important data gaps and new initiatives to close them, for example through space- and airborne sensors, (b) how various data sources and types can be integrated, (c) how uncertainty can be assessed in data-driven analyses and (d) how Big Data and machine learning approaches have opened new ways of investigating processes rather than simply describing patterns. We discuss how Big Data opens up new opportunities, but also poses new challenges to macroecological research. In the future, it will be essential to carefully assess data quality, the reproducibility of data compilation and analytical methods, and the communication of uncertainties. Major progress in the field will depend on the definition of data standards and workflows for macroecology, such that scientific quality and integrity are guaranteed, and collaboration in research projects is made easier.     

A Conceptual Mathematical Model of the Dynamic Self-Organisation of Distinct Cellular Organelles

Formation, degradation and renewal of cellular organelles is a dynamic process based on permanent budding, fusion and inter-organelle traffic of vesicles. These processes include many regulatory proteins such as SNAREs, Rabs and coats. Given this complex machinery, a controversially debated issue is the definition of a minimal set of generic mechanisms necessary to enable the self-organization of organelles differing in number, size and chemical composition. We present a conceptual mathematical model of dynamic organelle formation based on interacting vesicles which carry different types of fusogenic proteins (FP) playing the role of characteristic marker proteins. Our simulations (ODEs) show that a de novo formation of non-identical organelles, each accumulating a different type of FP, requires a certain degree of disproportionation of FPs during budding. More importantly however, the fusion kinetics must indispensably exhibit positive cooperativity among these FPs, particularly for the formation of larger organelles. We compared different types of cooperativity: sequential alignment of corresponding FPs on opposite vesicle/organelles during fusion and pre-formation of FP-aggregates (equivalent, e.g., to SNARE clusters) prior to fusion described by Hill kinetics. This showed that the average organelle size in the system is much more sensitive to the disproportionation strength of FPs during budding if the vesicular transport system gets along with a fusion mechanism based on sequential alignments of FPs. Therefore, pre-formation of FP aggregates within the membranes prior to fusion introduce robustness with respect to organelle size. Our findings provide a plausible explanation for the evolution of a relatively large number of molecules to confer specificity on the fusion machinery compared to the relatively small number involved in the budding process. Moreover, we could speculate that a specific cooperativity which may be described by Hill kinetics (aggregates or Rab/SNARE complex formation) is suitable if maturation/identity switching of organelles play a role (bistability).     

Continuous Solvent/Detergent Virus Inactivation Using a Packed‐Bed Reactor

Continuous virus inactivation (VI) remains one of the missing pieces while the biopharma industry moves toward continuous manufacturing. The challenges of adapting VI to the continuous operation are two‐fold: 1) achieving fluid homogeneity and 2) a narrow residence time distribution (RTD) for fluid incubation. To address these challenges, a dynamic active in‐line mixer and a packed‐bed continuous virus inactivation reactor (CVIR) are implemented, which act as a narrow RTD incubation chamber. The developed concept is applied using solvent/detergent (S/D) treatment for inactivation of two commonly used model viruses. The in‐line mixer is characterized and enables mixing of the viscous S/D chemicals to ±1.0% of the target concentration in a small dead volume. The reactor's RTD is characterized and additional control experiments confirm that the VI is due to the S/D action and not induced by system components. The CVIR setup achieves steady state rapidly before two reactor volumes and the logarithmic reduction values of the continuous inactivation process are identical to those obtained by the traditional batch operation. The packed‐bed reactor for continuous VI unites fully continuous processing with very low‐pressure drop and scalability.     

Dual Role of Mitochondrial Porin in Metabolite Transport across the Outer Membrane and Protein Transfer to the Inner Membrane

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Systematic identification of cancer driving signaling pathways based on mutual exclusivity of genomic alterations

We present a novel method for the identification of sets of mutually exclusive gene alterations in a given set of genomic profiles. We scan the groups of genes with a common downstream effect on the signaling network, using a mutual exclusivity criterion that ensures that each gene in the group significantly contributes to the mutual exclusivity pattern. We test the method on all available TCGA cancer genomics datasets, and detect multiple previously unreported alterations that show significant mutual exclusivity and are likely to be driver events.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0612-6) contains supplementary material, which is available to authorized users.     

Identification and Characterization of Circular RNAs As a New Class of Putative Biomarkers in Human Blood

Covalently closed circular RNA molecules (circRNAs) have recently emerged as a class of RNA isoforms with widespread and tissue specific expression across animals, oftentimes independent of the corresponding linear mRNAs. circRNAs are remarkably stable and sometimes highly expressed molecules. Here, we sequenced RNA in human peripheral whole blood to determine the potential of circRNAs as biomarkers in an easily accessible body fluid. We report the reproducible detection of thousands of circRNAs. Importantly, we observed that hundreds of circRNAs are much higher expressed than corresponding linear mRNAs. Thus, circRNA expression in human blood reveals and quantifies the activity of hundreds of coding genes not accessible by classical mRNA specific assays. Our findings suggest that circRNAs could be used as biomarker molecules in standard clinical blood samples.