Quantitative milk proteomics – Host responses to lipopolysaccharide‐mediated inflammation of bovine mammary gland

Intramammary infusion of lipopolysaccharide (LPS) in cows induces udder inflammation that partly simulates mastitis caused by infection with Gram‐negative bacteria. We have used this animal model to characterize the quantitiative response in the milk proteome during the time course before and immediately after the LPS challenge. Milk samples from three healthy cows collected 3 h before the LPS challenge were compared with milk samples collected 4 and 7 h after the LPS challenge, making it possible to describe the inflammatory response of individual cows. Quantitative protein profiles were obtained for 80 milk proteins, of which 49 profiles changed significantly for the three cows during LPS challenge. New information obtained in this study includes the quantified increase of apolipoproteins and other anti‐inflammatory proteins in milk, which are important for the cow's ability to balance the immune response, and the upregulation of both complement C3 and C4 indicates that more than one complement pathway could be activated during LPS‐induced mastitis. In the future, this analytical approach may provide valuable information about the differences in the ability of individual cows to resist and recover from mastitis.     

Synthesis and glycosidase inhibitory activity of 1-amino-3,6-anhydro-1-deoxy-d-sorbitol derivatives

3,6-Anhydro-1-(aryl or alkylamino)-1-deoxy-d-sorbitol derivatives have been prepared in four steps from isosorbide, a by-product from the starch industry. The inhibitory activities of these new compounds have been evaluated towards 13 glycosidases. A first lead-compound was identified, which inhibited β-N-acetylglucosaminidase from bovine kidney (82% inhibition at 1 mM).     

A high-throughput chemically induced inflammation assay in zebrafish

Background  

Studies on innate immunity have benefited from the introduction of zebrafish as a model system. Transgenic fish expressing fluorescent proteins in leukocyte populations allow direct, quantitative visualization of an inflammatory response in vivo. It has been proposed that this animal model can be used for high-throughput screens aimed at the identification of novel immunomodulatory lead compounds. However, current assays require invasive manipulation of fish individually, thus preventing high-content screening.     

The virtual ecologist approach: simulating data and observers

Ecologists carry a well‐stocked toolbox with a great variety of sampling methods, statistical analyses and modelling tools, and new methods are constantly appearing. Evaluation and optimisation of these methods is crucial to guide methodological choices. Simulating error‐free data or taking high‐quality data to qualify methods is common practice. Here, we emphasise the methodology of the ‘virtual ecologist’ (VE) approach where simulated data and observer models are used to mimic real species and how they are ‘virtually’ observed. This virtual data is then subjected to statistical analyses and modelling, and the results are evaluated against the ‘true’ simulated data. The VE approach is an intuitive and powerful evaluation framework that allows a quality assessment of sampling protocols, analyses and modelling tools. It works under controlled conditions as well as under consideration of confounding factors such as animal movement and biased observer behaviour. In this review, we promote the approach as a rigorous research tool, and demonstrate its capabilities and practical relevance. We explore past uses of VE in different ecological research fields, where it mainly has been used to test and improve sampling regimes as well as for testing and comparing models, for example species distribution models. We discuss its benefits as well as potential limitations, and provide some practical considerations for designing VE studies. Finally, research fields are identified for which the approach could be useful in the future. We conclude that VE could foster the integration of theoretical and empirical work and stimulate work that goes far beyond sampling methods, leading to new questions, theories, and better mechanistic understanding of ecological systems.