An Emerging Approach for Parallel Quantification of Intracellular Protozoan Parasites and Host Cell Characterization Using TissueFAXS Cytometry

Characterization of host-pathogen interactions is a fundamental approach in microbiological and immunological oriented disciplines. It is commonly accepted that host cells start to change their phenotype after engulfing pathogens. Techniques such as real time PCR or ELISA were used to characterize the genes encoding proteins that are associated either with pathogen elimination or immune escape mechanisms. Most of such studies were performed in vitro using primary host cells or cell lines. Consequently, the data generated with such approaches reflect the global RNA expression or protein amount recovered from all cells in culture. This is justified when all host cells harbor an equal amount of pathogens under experimental conditions. However, the uptake of pathogens by phagocytic cells is not synchronized. Consequently, there are host cells incorporating different amounts of pathogens that might result in distinct pathogen-induced protein biosynthesis. Therefore, we established a technique able to detect and quantify the number of pathogens in the corresponding host cells using immunofluorescence-based high throughput analysis. Paired with multicolor staining of molecules of interest it is now possible to analyze the infection profile of host cell populations and the corresponding phenotype of the host cells as a result of parasite load.     

Chemoenzymatic Site-Specific Labeling of Influenza Glycoproteins as a Tool to Observe Virus Budding in Real Time

The influenza virus uses the hemagglutinin (HA) and neuraminidase (NA) glycoproteins to interact with and infect host cells. While biochemical and microscopic methods allow examination of the early steps in flu infection, the genesis of progeny virions has been more difficult to follow, mainly because of difficulties inherent in fluorescent labeling of flu proteins in a manner compatible with live cell imaging. We here apply sortagging as a chemoenzymatic approach to label genetically modified but infectious flu and track the flu glycoproteins during the course of infection. This method cleanly distinguishes influenza glycoproteins from host glycoproteins and so can be used to assess the behavior of HA or NA biochemically and to observe the flu glycoproteins directly by live cell imaging.     

Biochemical evidence accumulates across neurons to drive a network-level eruption

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A case study for late Archean and Proterozoic biogeochemical iron‐ and sulphur cycling in a modern habitat—the Arvadi Spring

As a consequence of Earth's surface oxygenation, ocean geochemistry changed from ferruginous (iron(II)‐rich) into more complex ferro‐euxinic (iron(II)‐sulphide‐rich) conditions during the Paleoproterozoic. This transition must have had profound implications for the Proterozoic microbial community that existed within the ocean water and bottom sediment; in particular, iron‐oxidizing bacteria likely had to compete with emerging sulphur‐metabolizers. However, the nature of their coexistence and interaction remains speculative. Here, we present geochemical and microbiological data from the Arvadi Spring in the eastern Swiss Alps, a modern model habitat for ferro‐euxinic transition zones in late Archean and Proterozoic oceans during high‐oxygen intervals, which enables us to reconstruct the microbial community structure in respective settings for this geological era. The spring water is oxygen‐saturated but still contains relatively elevated concentrations of dissolved iron(II) (17.2 ± 2.8 μM) and sulphide (2.5 ± 0.2 μM) with simultaneously high concentrations of sulphate (8.3 ± 0.04 mM). Solids consisting of quartz, calcite, dolomite and iron(III) oxyhydroxide minerals as well as sulphur‐containing particles, presumably elemental S⁰, cover the spring sediment. Cultivation‐based most probable number counts revealed microaerophilic iron(II)‐oxidizers and sulphide‐oxidizers to represent the largest fraction of iron‐ and sulphur‐metabolizers in the spring, coexisting with less abundant iron(III)‐reducers, sulphate‐reducers and phototrophic and nitrate‐reducing iron(II)‐oxidizers. 16S rRNA gene 454 pyrosequencing showed sulphide‐oxidizing Thiothrix species to be the dominating genus, supporting the results from our cultivation‐based assessment. Collectively, our results suggest that anaerobic and microaerophilic iron‐ and sulphur‐metabolizers could have coexisted in oxygenated ferro‐sulphidic transition zones of late Archean and Proterozoic oceans, where they would have sustained continuous cycling of iron and sulphur compounds.     

<Emphasis Type="Italic">PLP1</Emphasis> Gene Variation Modulates Leftward and Rightward Functional Hemispheric Asymmetries

Molecular neurobiological factors determining corpus callosum physiology and anatomy have been suggested to be one of the major factors determining functional hemispheric asymmetries. Recently, it was shown that allelic variations in two myelin-related genes, the proteolipid protein 1 gene PLP1 and the contactin 1 gene CNTN1, are associated with differences in interhemispheric integration. Here, we investigated whether three single nucleotide polymorphisms that were associated with interhemispheric integration via the corpus callosum in a previous study also are relevant for functional hemispheric asymmetries. To this end, we tested more than 900 healthy adults with the forced attention dichotic listening task, a paradigm to assess language lateralization and its modulation by cognitive control processes. Moreover, we used the line bisection task, a paradigm to assess functional hemispheric asymmetries in spatial attention. We found that a polymorphism in PLP1, but not CNTN1, was associated with performance differences in both tasks. Both functional hemispheric asymmetries and their modulation by cognitive control processes were affected. These findings suggest that both left and right hemisphere dominant cognitive functions can be modulated by allelic variation in genes affecting corpus callosum structure. Moreover, higher order cognitive processes may be relevant parameters when investigating the molecular basis of hemispheric asymmetries.     

Smell the change: On the potential of gas‐chromatographic ion mobility spectrometry in ecosystem monitoring

Plant volatile organic compounds (pVOCs) are being recognized as an important factor in plant–environment interactions. Both the type and amount of the emissions appear to be heavily affected by climate change. A range of studies therefore has been directed toward understanding pVOC emissions, mostly under laboratory conditions (branch/leaf enclosure). However, there is a lack of rapid, sensitive, and selective analytical methods, and therefore, only little is known about VOC emissions under natural, outdoor conditions. An increased sensitivity and the identification of taxon‐specific patterns could turn VOC analysis into a powerful tool for the monitoring of atmospheric chemistry, ecosystems, and biodiversity, with far‐reaching relevance to the impact of climate change on pVOCs and vice versa. This study for the first time investigates the potential of ion mobility spectrometry coupled to gas‐chromatographic preseparation (GC‐IMS) to dramatically increase sensitivity and selectivity for continuous monitoring of pVOCs and to discriminate contributing plant taxa and their phenology. Leaf volatiles were analyzed for nine different common herbaceous plants from Germany. Each plant turned out to have a characteristic metabolite pattern. pVOC patterns in the field would thus reflect the composition of the vegetation, but also phenology (with herbaceous and deciduous plants contributing according to season). The technique investigated here simultaneously enables the identification and quantification of substances characteristic for environmental pollution such as industrial and traffic emissions or pesticides. GC‐IMS thus has an enormous potential to provide a broad range of data on ecosystem function. This approach with near‐continues measurements in the real plant communities could provide crucial insights on pVOC‐level emissions and their relation to climate and phenology and thus provide a sound basis for modeling climate change scenarios including pVOC emissions.