Metabolic modeling predicts specific gut bacteria as key determinants for Candida albicans colonization levels

Candida albicans is a leading cause of life-threatening hospital-acquired infections and can lead to Candidemia with sepsis-like symptoms and high mortality rates. We reconstructed a genome-scale C. albicans metabolic model to investigate bacterial-fungal metabolic interactions in the gut as determinants of fungal abundance. We optimized the predictive capacity of our model using wild type and mutant C. albicans growth data and used it for in silico metabolic interaction predictions. Our analysis of more than 900 paired fungal–bacterial metabolic models predicted key gut bacterial species modulating C. albicans colonization levels. Among the studied microbes, Alistipes putredinis was predicted to negatively affect C. albicans levels. We confirmed these findings by metagenomic sequencing of stool samples from 24 human subjects and by fungal growth experiments in bacterial spent media. Furthermore, our pairwise simulations guided us to specific metabolites with promoting or inhibitory effect to the fungus when exposed in defined media under carbon and nitrogen limitation. Our study demonstrates that in silico metabolic prediction can lead to the identification of gut microbiome features that can significantly affect potentially harmful levels of C. albicans.Subject terms: Fungi, Infectious diseases, Metagenomics, Gastrointestinal diseases, Microbiome     

Simulating small‐scale climate change effects–lessons from a short‐term field manipulation experiment on grassland arthropods

Climate change is expected to cause major consequences on biodiversity. Understanding species‐specific reactions, such as species shifts, species declines, and changes in population dynamics is a key issue to quantify large‐scale impacts of climate change on biotic communities. As it is often impossible or at least impracticable to conduct large‐scale experiments on biotic responses to climate change, studies at a smaller scale may be a useful alternative. In our study, we therefore tested responses of grassland arthropods (carabid beetles, spiders, grasshoppers) to simulated climate change in terms of species activity densities and diversity. We conducted a controlled field experiment by changing water and microclimatic conditions at a small scale (16 m²). Roof constructions were used to increase drought‐like conditions, whereas water supply was enhanced by irrigation. In all, 2 038 carabid beetles (36 species), 4 893 spiders (65 species), and 303 Orthoptera (4 species) were caught using pitfall traps from May to August, 2010. During our experiment, we created an artificial small‐scale climate change; and statistics revealed that these changes had short‐term effects on the total number of individuals and Simpson diversity of the studied arthropod groups. Moreover, our results showed that certain species might react very quickly to climate change in terms of activity densities, which in turn might influence diversity due to shifts in abundance patterns. Finally, we devised methodological improvements that may further enhance the validity of future studies.     

Distinct in vivo roles of secreted APP ectodomain variants APPsα and APPsβ in regulation of spine density,synaptic plasticity,and cognition

Increasing evidence suggests that synaptic functions of the amyloid precursor protein (APP), which is key to Alzheimer pathogenesis, may be carried out by its secreted ectodomain (APPs). The specific roles of APPsα and APPsβ fragments, generated by non‐amyloidogenic or amyloidogenic APP processing, respectively, remain however unclear. Here, we expressed APPsα or APPsβ in the adult brain of conditional double knockout mice (cDKO) lacking APP and the related APLP2. APPsα efficiently rescued deficits in spine density, synaptic plasticity (LTP and PPF), and spatial reference memory of cDKO mice. In contrast, APPsβ failed to show any detectable effects on synaptic plasticity and spine density. The C‐terminal 16 amino acids of APPsα (lacking in APPsβ) proved sufficient to facilitate LTP in a mechanism that depends on functional nicotinic α7‐nAChRs. Further, APPsα showed high‐affinity, allosteric potentiation of heterologously expressed α7‐nAChRs in oocytes. Collectively, we identified α7‐nAChRs as a crucial physiological receptor specific for APPsα and show distinct in vivo roles for APPsα versus APPsβ. This implies that reduced levels of APPsα that might occur during Alzheimer pathogenesis cannot be compensated by APPsβ.     

Optimization of continuous purification of recombinant patchoulol synthase from Escherichia coli with membrane adsorbers

The natural production of patchouli oil in developing countries cannot meet the increasing demand any more. This leads to socioecological consequences, such as the use of arable land, which is actually intended for food. Hence, the world market price increased up to $150/kg. An alternative is the biotechnological production of patchouli oil using a multiproduct sesquiterpene synthase, the patchoulol synthase (PTS). Here, we report the optimization of recombinant PTS purification from Escherichia coli lysate using continuous immobilized metal affinity chromatography. First, the purification conditions of the batch process were optimized in regard to optimal buffer composition and optimized chromatographic conditions. The best purification result was achieved with Co²⁺-immobilized metal affinity chromatography (Sartobind® IDA 75) with a triethanolamine buffer at pH 7, 0.5 M NaCl, 10% [vol/vol] glycerol, 5 mM MgCl₂ and 250 mM imidazole for product elution. This optimized method was then transferred to a continuous chromatography system using three membrane adsorber units (surface of 75 cm² each). Within 1.5 hr in total, 4.55 mg PTS with a final purity of 98% and recovery of 68% could be gained. The purified enzyme was used to produce 126 mg/L (-)-patchoulol from farnesyl pyrophosphate. Here, for the first time bioactive PTS was successfully purified using membrane adsorbers in a continuous downstream process.     

Metabolic costs of amino acid and protein production in Escherichia coli

Escherichia coli is the most popular microorganism for the production of recombinant proteins and is gaining increasing importance for the production of low-molecular weight compounds such as amino acids. The metabolic cost associated with the production of amino acids and (recombinant) proteins from glucose, glycerol and acetate was determined using three different computational techniques to identify those amino acids that put the highest burden on the biosynthetic machinery of E. coli. Comparing the costs of individual amino acids, we find that methionine is the most expensive amino acid in terms of consumed mol of ATP per molecule produced, while leucine is the most expensive amino acid when taking into account the cellular abundances of amino acids. Moreover, we show that the biosynthesis of a large number of amino acids from glucose and particularly from glycerol provides a surplus of energy, which can be used to balance the high energetic cost of amino acid polymerization.     

Does pollen limitation affect population growth of the endangered Dracocephalum austriacum L.?

Reproductive strategies can have significant consequences for the viability of plant populations. Still, the effects of lower fruit set due to pollen limitation on plant demography and population persistence have rarely been explored. The objectives of this study were to assess the ecological factors determining female reproductive success and to study the impact of pollen limitation on population growth of Dracocephalum austriacum L. (Lamiaceae), a critically endangered species with a discontinuous distribution across Europe. Despite the significant background information gathered on the population dynamics and genetic diversity of D. austriacum, little is known about its reproductive strategy and the effect it has on population growth. Thus, the reproductive system, pollinator assemblage and pollen limitation were studied in natural populations and the impact of pollen-limited seed production on population growth was assessed using existing transition matrix models. The results revealed that D. austriacum is protandrous self-compatible species that produces very few seeds in the absence of pollinators. The flowers are visited by several insects, including legitimate pollinators (e.g., Bombus hortorum, Osmia spp.) and nectar robbers (other Bombus spp., O. aurulenta). Fruit and seed production was significantly pollen-limited in all populations studied. However, despite the positive effect of pollen supplementation on seed production, the resulting increase in seed number did not significantly increase population growth rates in any of the studied populations. Hence, we conclude that populations are demographically stable and current natural seed production is sufficient for the species’ persistence.