Crystal structure of Diedel, a marker of the immune response of Drosophila melanogaster

Background

The Drosophila melanogaster gene CG11501 is up regulated after a septic injury and was proposed to act as a negative regulator of the JAK/STAT signaling pathway. Diedel, the CG11501 gene product, is a small protein of 115 residues with 10 cysteines.

Methodology/Principal Findings

We have produced Diedel in Drosophila S2 cells as an extra cellular protein thanks to its own signal peptide and solved its crystal structure at 1.15 Å resolution by SIRAS using an iodo derivative. Diedel is composed of two sub domains SD1 and SD2. SD1 is made of an antiparallel β-sheet covered by an α-helix and displays a ferredoxin-like fold. SD2 reveals a new protein fold made of loops connected by four disulfide bridges. Further structural analysis identified conserved hydrophobic residues on the surface of Diedel that may constitute a potential binding site. The existence of two conformations, cis and trans, for the proline 52 may be of interest as prolyl peptidyl isomerisation has been shown to play a role in several physiological mechanisms. The genome of D. melanogaster contains two other genes coding for proteins homologous to Diedel, namely CG43228 and CG34329. Strikingly, apart from Drosophila and the pea aphid Acyrthosiphon pisum, Diedel-related sequences were exclusively identified in a few insect DNA viruses of the Baculoviridae and Ascoviridae families.

Conclusion/Significance

Diedel, a marker of the Drosophila antimicrobial/antiviral response, is a member of a small family of proteins present in drosophilids, aphids and DNA viruses infecting lepidopterans. Diedel is an extracellular protein composed of two sub-domains. Two special structural features (hydrophobic surface patch and cis/trans conformation for proline 52) may indicate a putative interaction site, and support an extra cellular signaling function for Diedel, which is in accordance with its proposed role as negative regulator of the JAK/STAT signaling pathway.     

A large-scale stream benthic diatom database

A relational database linking benthic diatom records, taxonomic nomenclature including synonyms, and corresponding environmental data has been built in MS Access. It allowed flexible and long-term use of a relatively important amount of data (∼3000 records) gathered in the framework of the EC-funded PAEQANN project, gathering precise and documented information both about benthic diatoms and quantitative or semi-quantitative environmental data. Such a database has been shown to be a useful tool for the definition of benthic diatom typology at a multi-regional scale, the prediction of the impact of environmental characteristics on the structure of diatom communities, and additionally for a new insight on the auto-ecology of some taxa. This database could serve as a template for further work on diatoms and, after some implementation, on other freshwater communities. It could also be the basis for wider typology of stream diatoms, extended to other regions.     

Efficiency of population structures for mapping of Mendelian and imprinted quantitative trait loci in outbred pigs using variance component methods

In a simulation study different designs for a pure line pig population were compared for efficiency of mapping QTL using the variance component method. Phenotypes affected by a Mendelian QTL, a paternally expressed QTL, a maternally expressed QTL or by a QTL without an effect were simulated. In all alternative designs 960 progeny were phenotyped. Given the limited number of animals there is an optimum between the number of families and the family size. Estimation of Mendelian and parentally expressed QTL is more efficient in a design with large family sizes. Too small a number of sires should be avoided to minimize chances of sires to be non-segregating. When a large number of families is used, the number of haplotypes increases which reduces the accuracy of estimating the QTL effect and thereby reduces the power to show a significant QTL and to correctly position the QTL. Dense maps allow for smaller family size due to exploitation of LD-information. Given the different possible modes of inheritance of the QTL using 8 to16 boars, two litters per dam was optimal with respect to determining significance and correct location of the QTL for a data set consisting of 960 progeny. The variance component method combining linkage disequilibrium and linkage analysis seems to be an appropriate choice to analyze data sets which vary in marker density and which contain complex family structures.     

The effect of using approximate gametic variance covariance matrices on marker assisted selection by BLUP

Under additive inheritance, the Henderson mixed model equations (HMME) provide an efficient approach to obtaining genetic evaluations by marker assisted best linear unbiased prediction (MABLUP) given pedigree relationships, trait and marker data. For large pedigrees with many missing markers, however, it is not feasible to calculate the exact gametic variance covariance matrix required to construct HMME. The objective of this study was to investigate the consequences of using approximate gametic variance covariance matrices on response to selection by MABLUP. Two methods were used to generate approximate variance covariance matrices. The first method (Method A) completely discards the marker information for individuals with an unknown linkage phase between two flanking markers. The second method (Method B) makes use of the marker information at only the most polymorphic marker locus for individuals with an unknown linkage phase. Data sets were simulated with and without missing marker data for flanking markers with 2, 4, 6, 8 or 12 alleles. Several missing marker data patterns were considered. The genetic variability explained by marked quantitative trait loci (MQTL) was modeled with one or two MQTL of equal effect. Response to selection by MABLUP using Method A or Method B were compared with that obtained by MABLUP using the exact genetic variance covariance matrix, which was estimated using 15 000 samples from the conditional distribution of genotypic values given the observed marker data. For the simulated conditions, the superiority of MABLUP over BLUP based only on pedigree relationships and trait data varied between 0.1% and 13.5% for Method A, between 1.7% and 23.8% for Method B, and between 7.6% and 28.9% for the exact method. The relative performance of the methods under investigation was not affected by the number of MQTL in the model.     

BAC libraries construction from the ancestral diploid genomes of the allotetraploid cultivated peanut

Background

Cultivated peanut, Arachis hypogaea is an allotetraploid of recent origin, with an AABB genome. In common with many other polyploids, it seems that a severe genetic bottle-neck was imposed at the species origin, via hybridisation of two wild species and spontaneous chromosome duplication. Therefore, the study of the genome of peanut is hampered both by the crop's low genetic diversity and its polyploidy. In contrast to cultivated peanut, most wild Arachis species are diploid with high genetic diversity. The study of diploid Arachis genomes is therefore attractive, both to simplify the construction of genetic and physical maps, and for the isolation and characterization of wild alleles. The most probable wild ancestors of cultivated peanut are A. duranensis and A. ipaënsis with genome types AA and BB respectively.

Results

We constructed and characterized two large-insert libraries in Bacterial Artificial Chromosome (BAC) vector, one for each of the diploid ancestral species. The libraries (AA and BB) are respectively c. 7.4 and c. 5.3 genome equivalents with low organelle contamination and average insert sizes of 110 and 100 kb. Both libraries were used for the isolation of clones containing genetically mapped legume anchor markers (single copy genes), and resistance gene analogues.

Conclusion

These diploid BAC libraries are important tools for the isolation of wild alleles conferring resistances to biotic stresses, comparisons of orthologous regions of the AA and BB genomes with each other and with other legume species, and will facilitate the construction of a physical map.

     

Can Nep1-like proteins form oligomers?

Nep1-like proteins (NLPs) are a novel family of microbial elicitors of plant necrosis that induce a hypersensitive-like response in dicot plants. The spatial structure and role of these proteins are yet unknown. In a paper published in BMC Plant Biology (2008; 8:50) we have proposed that the core region of Nep1-like proteins (NLPs) belong to the Cupin superfamily. Based on what is known about the Cupin superfamily, in this addendum to the paper we discuss how NLPs could form oligomers.Key words: quaternary structure, necrosis and ethylene inducing proteins, NLPs, MpNEP1, MpNEP2, NPP1, Moniliophthora perniciosa, Phytophthora parasiticaCupins may be organized as monomers, dimers, hexamers and octamers of β-barrel domains.¹ To the best of our knowledge trimers have not been detected yet. The interaction of two monomers building up a dimeric structure is basically performed by three types of interactions: hydrophobic interactions between β-strands in different subunits, salt bridges and hydrogen bonds between β-strands. In cupin dimers, the hydrophobic interactions occur between two βI strands in different subunits (Fig. 1A and B). This strand represents the central axis of rotation of the dimer as one residue in βI interacts with the corresponding residue in the other subunit (Fig. 1B). Therefore, all residues in βI must be hydrophobic, as one residue interacts with the other subunit and the next one in the sequence interacts with the interior of the protein. Charged residues in βI would disrupt such interactions. Most cupin dimers have strong hydrophobic residues such as tryptophan (W), phenylalanine (F) and methionine (M) pointing towards the own subunit (↓), while small hydrophobic residues such as leucine (L), isoleucine (I), and valine (V) point to the other subunit (↑). A particular case is leucine that interacts with other subunits, for instance, βI = liaW (positions 217–220 in Fig. 1B) and βI = LVsw of type I and II NLP consensuses, respectively. Therefore, the pattern of hydropathicity suggests that the side chain orientation is βI = l217 ↑ i218 ↓ a219 ↑ W220 ↓ d221 ↑. However we observe that just after βI there is a charged residue (aspartate D221) which would point outwards disrupting the dimer or at least making it less stable. It is interesting to observe that the requirement for a negatively charged residue at this last position is very high: 96% of all type I NLPs contains an aspartate (D) or glutamate (E) indicating an important role for it, maybe in avoiding dimerization of the NLPs. A second interesting hypothesis is as follows: several cupins are oxygenases, decarboxylases, etc. and use a negatively charged residue, such as aspartate or glutamate as proton donor.¹ Now, if the alternate pattern of side chains of the residues is βI = l217 ↓ i218 ↑ a219 ↓ W220 ↑ d221 ↓, instead of the previous one, then the aspartate or glutamate residue would point to the hydrophobic pocket and would be positioned to interact with the metal ion, as in cupins with enzymatic activity. However, there are no experimental evidences that the NLPs have enzymatic activity.Open in a separate windowFigure 1(A) Three-dimensional structure prediction for type I NLP consensus, (B) Interface between two βI strands in type I NLP consensus. From the left to the right: EF-coil with the conserved residue H162, βC and βH strands (superposed) with the conserved histidines H133 and H135 in βC, H193 and leucine L195 in βH, W220 in βI and W118 in βB. The strands in the right subunit follow the same pattern but rotated.The second type of interaction is salt bridges between charged residues in different subunits. Analyzing all interacting side chains in the 1VJ2 protein (dimer), we verify that the charged side chains of N35 and E57 (numbers in original structure) are only 2.72 Å apart. In the NLPs, this corresponds to N108^36% (Q108^60%) at the border of βB and E138^98%. The negatively charged residue D125 helps to correct the orientation of the subunits in relation to each other avoiding any disorientation. The high conservation level of these residues suggests that NLPs are dimeric structures. However, as we will see next, only hydrophobic and charged interactions are not enough to build a dimer.Garcia et al. (2007)² have used small angle X-ray scattering (SAXS) to show that, in solution, at low concentrations (<2 mg/ml) the two copies of the NLPs of Moniliophthora perniciosa, MpNEP1 and MpNEP2, exist as dimers and monomers, respectively. The same technique showed that at higher concentrations, >5 mg/ml, both proteins exist as dimers, as is the case for PpNPP1.² They also reported, based on electrophoresis analysis, that PpNPP1 and MpNEP1 exist as oligomers and MpNEP2 as monomers.² However, experiments with the PpNPP1 in size exclusion chromatography using myoglobin as size standard suggest that PpNPP1 is a monomer.³ Figure 2 compares MpNEP1, MpNEP2 and PpNPP1, where the most relevant differences in sequence are marked with asterisks (*) and are possibly related to the differences in oligomeric properties between MpNEP1 and PpNPP1 with MpNEP2. These positions are methionine M27 and leucine L35, which occur only in MpNEP2, glycine G250, which occurs only in MpNEP2 and NEP1 (Fusarium oxysporum) and lysine K31, which occurs only MpNEP2, {"type":"entrez-protein","attrs":{"text":"BAB04114","term_id":"10173008"}}BAB04114 (Bacillus halodurans) and {"type":"entrez-protein","attrs":{"text":"AAU23136","term_id":"52003194"}}AAU23136 (Bacillus licheniformis). The other residues are aspartate D28, which occurs 9 times and alanine A37 which occurs 7 times of all investigated NLPs. Thus, the sequence mdHDkiakl at the start of the NLPs seems to explain the monomeric state of MpNEP2, although at higher concentrations they form dimers. Besides the weak hydrophobic interactions, dimeric cupins and bicupins (two β barrels in the same sequence building up a dimeric-like 4d-structure) are stable structures (see Fig. 1 in ref. ⁴). By aggregating the first β-strand in the start domain of one β-barrel to the ABIDG β-sheet of the other β-barrel, composing a big ABIDGY β-sheet (Y is the first β-strand). For instance, using the bicupin 1L3J (oxalate decarboxylase) as template, the low confidence level β-strand at position 26–33 (v in H29D30 avv) in type I NLPs corresponds to the first β-strand. Since this proceeds from both barrels they can build a stable structure (see Fig. 1 in ref. ⁴). The quaternary structure is related to the presence of interaction residues in the BID β-sheet of the cupin structure. These are present in the NLPs and would enable them to form dimers.Open in a separate windowFigure 2Alignment of type I NLP consensus, PpNPP1, MpNEP1 and MpNEP2. Solid line boxes are β-strands, double line boxes are α-helices. The sequence positions marked with asterisks (*) are possibly related to the differences in oligomeric properties between MpNEP1 and PpNPP1 with MpNEP2.     

Toponomics analysis of functional interactions of the ubiquitin ligase PAM (Protein Associated with Myc) during spinal nociceptive processing

Protein associated with Myc (PAM) is a giant E3 ubiquitin ligase of 510 kDa. Although the role of PAM during neuronal development is well established, very little is known about its function in the regulation of synaptic strength. Here we used multiepitope ligand cartography (MELC) to study protein network profiles associated with PAM during the modulation of synaptic strength. MELC is a novel imaging technology that utilizes biomathematical tools to describe protein networks after consecutive immunohistochemical visualization of up to 100 proteins on the same sample. As an in vivo model to modulate synaptic strength we used the formalin test, a common model for acute and inflammatory pain. MELC analysis was performed with 37 different antibodies or fluorescence tags on spinal cord slices and led to the identification of 1390 PAM-related motifs that distinguish untreated and formalin-treated spinal cords. The majority of these motifs related to ubiquitin-dependent processes and/or the actin cytoskeleton. We detected an intermittent colocalization of PAM and ubiquitin with TSC2, a known substrate of PAM, and the glutamate receptors mGluR5 and GLUR1. Importantly these complexes were detected exclusively in the presence of F-actin. A direct PAM/F-actin interaction was confirmed by colocalization and cosedimentation. The binding of PAM toward F-actin varied strongly between the PAM splice forms found in rat spinal cords. PAM did not ubiquitylate actin or alter actin polymerization and depolymerization. However, F-actin decreased the ubiquitin ligase activity of purified PAM. Because PAM activation is known to involve its translocation, the binding of PAM to F-actin may serve to control its subcellular localization as well as its activity. Taken together we show that defining protein network profiles by topological proteomics analysis is a useful tool to identify previously unknown protein/protein interactions that underlie synaptic processes.     

Local spread of classical swine fever upon virus introduction into The Netherlands: Mapping of areas at high risk

Background

In the recent past, the introduction of Classical Swine Fever Virus (CSFV) followed by between-herd spread has given rise to a number of large epidemics in The Netherlands and Belgium. Both these countries are pork-exporting countries. Particularly important in these epidemics has been the occurrence of substantial "neighborhood transmission" from herd to herd in the presence of base-line control measures prescribed by EU legislation. Here we propose a calculation procedure to map out "high-risk areas" for local between-herd spread of CSFV as a tool to support decision making on prevention and control of CSFV outbreaks. In this procedure the identification of such areas is based on an estimated inter-herd distance dependent probability of neighborhood transmission or "local transmission". Using this distance-dependent probability, we derive a threshold value for the local density of herds. In areas with local herd density above threshold, local transmission alone can already lead to epidemic spread, whereas in below-threshold areas this is not the case. The first type of area is termed 'high-risk' for spread of CSFV, while the latter type is termed 'low-risk'.

Results

As we show for the case of The Netherlands, once the distance-dependent probability of local transmission has been estimated from CSFV outbreak data, it is possible to produce a map of the country in which areas of high-risk herds and of low-risk herds are identified. We made these maps even more informative by estimating border zones between the two types of areas. In these border zones the risk of local transmission of infection to a nearby high-risk area exceeds a certain level.

Conclusion

The risk maps provide an easily understandable visualization of the spatial heterogeneities in transmission risk. They serve as a tool for area-specific designs of control strategies, and possibly also for spatial planning of areas where livestock farming is allowed. Similar risk maps can in principle be constructed for other highly-transmissible livestock infections that spread via neighborhood transmission.