A plant pathogen modulates the effects of secondary metabolites on the performance and immune function of an insect herbivore

Host plant chemical composition critically shapes the performance of insect herbivores feeding on them. Some insects have become specialized on plant secondary metabolites, and even use them to their own advantage such as defense against predators. However, infection by plant pathogens can seriously alter the interaction between herbivores and their host plants. We tested whether the effects of the plant secondary metabolites, iridoid glycosides (IGs), on the performance and immune response of an insect herbivore are modulated by a plant pathogen. We used the IG‐specialized Glanville fritillary butterfly Melitaea cinxia, its host plant Plantago lanceolata, and the naturally occurring plant pathogen, powdery mildew Podosphaera plantaginis, as model system. Pre‐diapause larvae were fed on P. lanceolata host plants selected to contain either high or low IGs, in the presence or absence of powdery mildew. Larval performance was measured by growth rate, survival until diapause, and by investment in immunity. We assessed immunity after a bacterial challenge in terms of phenoloxidase (PO) activity and the expression of seven pre‐selected insect immune genes (qPCR). We found that the beneficial effects of constitutive leaf IGs, that improved larval growth, were significantly reduced by mildew infection. Moreover, mildew presence downregulated one component of larval immune response (PO activity), suggesting a physiological cost of investment in immunity under suboptimal conditions. Yet, feeding on mildew‐infected leaves caused an upregulation of two immune genes, lysozyme and prophenoloxidase. Our findings indicate that a plant pathogen can significantly modulate the effects of secondary metabolites on the growth of an insect herbivore. Furthermore, we show that a plant pathogen can induce contrasting effects on insect immune function. We suspect that the activation of the immune system toward a plant pathogen infection may be maladaptive, but the actual infectivity on the larvae should be tested.     

Picosecond excitation energy transfer of allophycocyanin studied in solution and in crystals

Cyanobacteria perform photosynthesis with the use of large light-harvesting antennae called phycobilisomes (PBSs). These hemispherical PBSs contain hundreds of open-chain tetrapyrrole chromophores bound to different peptides, providing an arrangement in which excitation energy is funnelled towards the PBS core from where it can be transferred to photosystem I and/or photosystem II. In the PBS core, many allophycocyanin (APC) trimers are present, red-light-absorbing phycobiliproteins that covalently bind phycocyanobilin (PCB) chromophores. APC trimers were amongst the first light-harvesting complexes to be crystallized. APC trimers have two spectrally different PCBs per monomer, a high- and a low-energy pigment. The crystal structure of the APC trimer reveals the close distance (~21 Å) between those two chromophores (the distance within one monomer is ~51 Å) and this explains the ultrafast (~1 ps) excitation energy transfer (EET) between them. Both chromophores adopt a somewhat different structure, which is held responsible for their spectral difference. Here we used spectrally resolved picosecond fluorescence to study EET in these APC trimers both in crystallized and in solubilized form. We found that not all closely spaced pigment couples consist of a low- and a high-energy pigment. In ~10% of the cases, a couple consists of two high-energy pigments. EET to a low-energy pigment, which can spectrally be resolved, occurs on a time scale of tens of picoseconds. This transfer turns out to be three times faster in the crystal than in the solution. The spectral characteristics and the time scale of this transfer component are similar to what have been observed in the whole cells of Synechocystis sp. PCC 6803, for which it was ascribed to EET from C-phycocyanin to APC. The present results thus demonstrate that part of this transfer should probably also be ascribed to EET within APC trimers.     

Genomic organization of four β-1,4-endoglucanase genes in plant-parasitic cyst nematodes and its evolutionary implications

The genomic organization of genes encoding β-1,4-endoglucanases (cellulases) from the plant-parasitic cyst nematodes Heterodera glycines and Globodera rostochiensis (HG-eng1, Hg-eng2, GR-eng1, and GR-eng2) was investigated. HG-eng1 and GR-eng1 both contained eight introns and structural domains of 2151 and 2492 bp, respectively. HG-eng2 and GR-eng2 both contained seven introns and structural domains of 2324 and 2388 bp, respectively. No significant similarity in intron sequence or size was observed between HG-eng1 and HG-eng2, whereas the opposite was true between GR-eng1 and GR-eng2. Intron positions among all four cyst nematode cellulase genes were conserved identically in relation to the predicted amino acid sequence. HG-eng1, GR-eng1, and GR-eng2 had several introns demarcated by 5′-GC…AG-3′ in the splice sites, and all four nematode cellulase genes had the polyadenylation and cleavage signal sequence 5′-GAUAAA-3′—both rare occurences in eukaryotic genes. The 5′- flanking regions of each nematode cellulase gene, however, had signature sequences typical of eukaryotic promoter regions, including a TATA box, bHLH-type binding sites, and putative silencer, repressor, and enhancer elements. Database searches and subsequent phylogenetic comparison of the catalytic domain of the nematode cellulases placed the nematode genes in one group, with Family 5, subfamily 2, glycosyl hydrolases from Scotobacteria and Bacilliaceae as the most homologous groups. The overall amino acid sequence identity among the four nematode cellulases was from 71 to 83%, and the amino acid sequence identity to bacterial Family 5 cellulases ranged from 33 to 44%. The eukaryotic organization of the four cyst nematode cellulases suggests that they share a common ancestor, and their strong homology to prokaryotic glycosyl hydrolases may be indicative of an ancient horizontal gene transfer.     

Peroxisome fission in Hansenula polymorpha requires Mdv1 and Fis1, two proteins also involved in mitochondrial fission

We show that Mdv1 and Caf4, two components of the mitochondrial fission machinery in Saccharomyces cerevisiae , also function in peroxisome proliferation. Deletion of MDV1 , CAF4 or both, however, had only a minor effect on peroxisome numbers at peroxisome-inducing growth conditions, most likely related to the fact that Vps1 – and not Dnm1 – is the key player in peroxisome fission in this organism. In contrast, in Hansenula polymorpha , which has only a Dnm1-dependent peroxisome fission machinery, deletion of MDV1 led to a drastic reduction of peroxisome numbers. This phenotype was accompanied by a strong defect in mitochondrial fission. The MDV1 paralog CAF4 is absent in H. polymorpha . In wild-type H. polymorpha , cells Dnm1–mCherry and green fluorescent protein (GFP)–Mdv1 colocalize in spots that associate with both peroxisomes and mitochondria. Furthermore, Fis1 is essential to recruit Mdv1 to the peroxisomal and mitochondrial membrane. However, formation of GFP–Mdv1 spots – and related to this normal organelle fission – is strictly dependent on the presence of Dnm1. In dnm1 cells, GFP–Mdv1 is dispersed over the surface of peroxisomes and mitochondria. Also, in H. polymorpha mdv1 or fis1 cells, the number of Dnm1–GFP spots is strongly reduced. These spots still associate to organelles but are functionally inactive.     

Homo-FRET Imaging Enables Quantification of Protein Cluster Sizes with Subcellular Resolution

Fluorescence-anisotropy-based homo-FRET detection methods can be employed to study clustering of identical proteins in cells. Here, the potential of fluorescence anisotropy microscopy for the quantitative imaging of protein clusters with subcellular resolution is investigated. Steady-state and time-resolved anisotropy detection and both one- and two-photon excitation methods are compared. The methods are evaluated on cells expressing green fluorescent protein (GFP) constructs that contain one or two FK506-binding proteins. This makes it possible to control dimerization and oligomerization of the constructs and yields the experimental relation between anisotropy and cluster size. The results show that, independent of the experimental method, the commonly made assumption of complete depolarization after a single energy transfer step is not valid here. This is due to a nonrandom relative orientation of the fluorescent proteins. Our experiments show that this relative orientation is restricted by interactions between the GFP barrels. We describe how the experimental relation between anisotropy and cluster size can be employed in quantitative cluster size imaging experiments of other GFP fusions. Experiments on glycosylphosphatidylinisotol (GPI)-anchored proteins reveal that GPI forms clusters with an average size of more than two subunits. For epidermal growth factor receptor (EGFR), we observe that ∼40% of the unstimulated receptors are present in the plasma membrane as preexisting dimers. Both examples reveal subcellular heterogeneities in cluster size and distribution.     

Pesticide ecotoxicological effect factors and their uncertainties for freshwater ecosystems

Background, aim, and scope  Characterization factors for ecotoxicity in the Life Cycle Impact Assessment (LCIA) are used to convert emissions into ecotoxicological impacts. Deriving them involves a fate and an effect analysis step. The fate factor quantifies the change in environmental concentration per unit of emission, while the effect factor quantifies the change in impact on the ecosystem per unit of environmental concentration. This paper calculates freshwater ecotoxicological effect factors for 397 pesticides belonging to 11 pesticide-specific toxic modes of action (TMoA), such as acetylcholinesterase inhibition and photosynthesis inhibition. Moreover, uncertainties in the effect factors due to uncertain background concentrations and due to limited toxicity data are quantified. Methods  To calculate median ecotoxicological effect factors (EEFs), toxic pressure assessments were made, based on the species sensitivity distribution—and the multisubstance potentially affected fraction—concept. The EEF quantifies an estimate of the fraction of species that is probably affected due to a marginal change in concentration of a pesticide. EEFs were divided into a TMoA-specific and a chemical-specific part, which were calculated on the basis of physicochemical properties, emissions, and toxicity data. Propagation of parameter uncertainty in the EEFs and the TMoA- and chemical-specific parts was quantified by Monte Carlo simulation and results were reported as 90% confidence intervals. Results  Median EEFs range from 2·10⁻³ to 7·10⁶ l/g. Uncertainty in the TMoA-specific part is dominated by uncertainty in the TMoA-specific spread in species sensitivity and by uncertainty in the effective toxicity of a TMoA. Uncertainty in the chemical-specific part of the EEFs depends on the number of species for which toxicity data are available to calculate average toxicity (n _s) and ranges from a median uncertainty of 2.6 orders of magnitude for n _s = 2 to one order of magnitude for n _s ≥ 4. The TMoA-specific effect factor for systemic fungicides shows the largest uncertainty range. For seven TMoAs, uncertainty ranges of the TMoA-specific effect factor are less than two orders of magnitude. For the other four TMoAs, the EEF uncertainty range is between two and eight orders of magnitude. For the chemical-specific part of the EEFs, we found that variation in uncertainty readily decreases for pesticides for which toxicity data are available for at least three species. Discussion  The same parameters that contributed most to uncertainty were found for pesticides as were found before for high-production-volume chemicals. However, uncertainty in concentrations of pesticides was lower. TMoA-specific factors obtained with the applied nonlinear method differ up to nine orders of magnitude from the factor of 0.5, which is used in the linear method. With the applied method, a distinction in EEFs can be made among different TMoAs. Conclusions   Ecotoxicological effect factors are presented, including overviews of their uncertainty ranges and the main contributors to uncertainty. The applied nonlinear method provides the possibility to quantify parameter uncertainty in the TMoA-specific part of the ecotoxicological effect factor, which is helpful to get more insight in how uncertainty in ecotoxicological characterization factors can be reduced. Recommendations and perspectives  The calculated uncertainty ranges can be included in life cycle assessment (LCA) case studies, which allows for better interpretation of LCA results obtained with the EEFs. To put the uncertainty in effect factors into perspective within LCIA, more information on the uncertainty in fate factors should be derived. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

PACSINs bind to the TRPV4 cation channel. PACSIN 3 modulates the subcellular localization of TRPV4

TRPV4 is a cation channel that responds to a variety of stimuli including mechanical forces, temperature, and ligand binding. We set out to identify TRPV4-interacting proteins by performing yeast two-hybrid screens, and we isolated with the avian TRPV4 amino terminus the chicken orthologues of mammalian PACSINs 1 and 3. The PACSINs are a protein family consisting of three members that have been implicated in synaptic vesicular membrane trafficking and regulation of dynamin-mediated endocytotic processes. In biochemical interaction assays we found that all three murine PACSIN isoforms can bind to the amino terminus of rodent TRPV4. No member of the PACSIN protein family was able to biochemically interact with TRPV1 and TRPV2. Co-expression of PACSIN 3, but not PACSINs 1 and 2, shifted the ratio of plasma membrane-associated versus cytosolic TRPV4 toward an apparent increase of plasma membrane-associated TRPV4 protein. A similar shift was also observable when we blocked dynamin-mediated endocytotic processes, suggesting that PACSIN 3 specifically affects the endocytosis of TRPV4, thereby modulating the subcellular localization of the ion channel. Mutational analysis shows that the interaction of the two proteins requires both a TRPV4-specific proline-rich domain upstream of the ankyrin repeats of the channel and the carboxyl-terminal Src homology 3 domain of PACSIN 3. Such a functional interaction could be important in cell types that show distribution of both proteins to the same subcellular regions such as renal tubule cells where the proteins are associated with the luminal plasma membrane.