Regulators of complement activity mediate inhibitory mechanisms through a common C3b‐binding mode

Regulators of complement activation (RCA) inhibit complement‐induced immune responses on healthy host tissues. We present crystal structures of human RCA (MCP, DAF, and CR1) and a smallpox virus homolog (SPICE) bound to complement component C3b. Our structural data reveal that up to four consecutive homologous CCP domains (i–iv), responsible for inhibition, bind in the same orientation and extended arrangement at a shared binding platform on C3b. Large sequence variations in CCP domains explain the diverse C3b‐binding patterns, with limited or no contribution of some individual domains, while all regulators show extensive contacts with C3b for the domains at the third site. A variation of ~100° rotation around the longitudinal axis is observed for domains binding at the fourth site on C3b, without affecting the overall binding mode. The data suggest a common evolutionary origin for both inhibitory mechanisms, called decay acceleration and cofactor activity, with variable C3b binding through domains at sites ii, iii, and iv, and provide a framework for understanding RCA disease‐related mutations and immune evasion.     

Production and characterization of polyclonal and monoclonal antibodies against Aflatoxin B1 oxime-BSA in an enzyme-linked immunosorbent assay

From a single aflatoxin B₁ oxime — bovine serum albumin conjugate, polyclonal and monoclonal antibody preparations were produced. The four rabbit polyclonal antisera were specific for aflatoxin Bi in a microtitration plate enzyme — linked immunosorbent assay. The monoclonal antibodies showed a wide range of differing specificities, recognizing, for example, aflatoxins B₁, B₂, G₁ and G₂; B₁ and B₂; B₁ and G₁; and G₁ alone. No antibody preparations reacted with aflatoxin M₁. The significance of these results to the strategy of anti-aflatoxin antibody production for use in quantitative enzyme immunoassays is discussed.     

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.     

Differential responsiveness to immunoablative therapy in refractory rheumatoid arthritis is associated with level and avidity of anti-cyclic citrullinated protein autoantibodies: a case study

In order to identify pathogenic correlates of refractory rheumatoid arthritis (RA), antibodies against anti-cyclic citrullinated protein (ACPAs) were investigated in RA patients in whom the dysregulated immune system had been ablated by high-dose chemotherapy (HDC) and autologous haematopoietic stem cell transplantation (HSCT). Six patients with refractory RA were extensively characterized in terms of levels of total immunoglobulins, RA-specific autoantibodies (ACPAs and rheumatoid factor) and antibodies against rubella, tetanus toxoid (TT) and phosphorylcholine before and after HDC plus HSCT. Additionally, the avidity of ACPAs was measured before and after treatment and compared with the avidity of TT antibodies following repeated immunizations. Synovial biopsies were obtained by arthroscopy before HDC plus HSCT, and analyzed by immunohistochemistry. In the three patients with clinically long-lasting responses to HDC plus HSCT (median 423 days), significant reductions in ACPA-IgG levels after therapy were observed (median level dropped from 215 to 34 arbitrary units/ml; P = 0.05). In contrast, stable ACPA-IgG levels were observed in three patients who relapsed shortly after HDC plus HSCT (median of 67 days). Clinical responders had ACPA-IgG of lower avidity (r = 0.75; P = 0.08) and higher degree of inflammation histologically (r = 0.73; P = 0.09). Relapse (after 38 to 530 days) in all patients was preceded by rising levels of low avidity ACPA-IgG (after 30 to 388 days), in contrast to the stable titres of high avidity TT antibodies. In conclusion, humoral autoimmune responses were differentially modulated by immunoablative therapy in patients with synovial inflammation and low avidity ACPA-IgG autoantibodies as compared with patients with high levels of high avidity ACPA-IgG. The distinct clinical disease course after immunoablative therapy based on levels and avidity of ACPA-IgG indicates that refractory RA is not a single disease entity.     

Enrichment of DNRA bacteria in a continuous culture

Denitrification and dissimilatory nitrate reduction to ammonium (DNRA) are competing microbial nitrate-reduction processes. The occurrence of DNRA has been shown to be effected qualitatively by various parameters in the environment. A more quantitative understanding can be obtained using enrichment cultures in a laboratory reactor, yet no successful DNRA enrichment culture has been described. We showed that a stable DNRA-dominated enrichment culture can be obtained in a chemostat system. The enrichment was based on the hypothesis that nitrate limitation is the dominant factor in selecting for DNRA. First, a conventional denitrifying culture was enriched from activated sludge, with acetate and nitrate as substrates. Next, the acetate concentration in the medium was increased to obtain nitrate-limiting conditions. As a result, conversions shifted from denitrification to DNRA. In this selection of a DNRA culture, two important factors were the nitrate limitation and a relatively low dilution rate (0.026 h⁻¹). The culture was a highly enriched population of Deltaproteobacteria most closely related to Geobacter lovleyi, based on 16S rRNA gene sequencing (97% similarity). We established a stable and reproducible cultivation method for the enrichment of DNRA bacteria in a continuously operated reactor system. This enrichment method allows to further investigate the DNRA process and address the factors for competition between DNRA and denitrification, or other N-conversion pathways.     

Insights from Streptococcus pneumoniae glucose kinase structural model

Streptococcus pneumonia is the common cause of sepsis and meningitis. Emergence of multiple antibiotic resistant strains in the community‐acquired bacterium is catastrophic. Glucose kinase (GLK) is a regulatory enzyme capable of adding phosphate group to glucose in the first step of streptomycin biosynthesis. The activity of glucose kinase was regulated by the Carbon Catabolite Repression (CCR) system. Therefore, it is important to establish the structure‐function relation of GLK in S. pneumoniae. However, a solved structure for S. pneumoniae GLK is not available at the protein data bank (PDB). Therefore, we created a model of GLK from S. pnemoniae using the X‐ray structure of Glk from E. faecalis as template with MODELLER (a comparative modeling program). The model was validated using protein structure checking tools such as PROCHECK, WHAT IF and ProSA for reliability. The active site amino acid Asp114 in the template is retained in S. pneumoniae GLK model (Asp115). Solvent accessible surface area (ASA) analysis of the GLK model showed that known key residues playing important role in active site for ligand binding and metal ion binding are buried and hence not accessible to solvent. The information thus discussed provides insight to the molecular understanding of glucose kinase in S. pneumoniae.     

Genomic selection of purebreds for crossbred performance

Background

One of the main limitations of many livestock breeding programs is that selection is in pure breeds housed in high-health environments but the aim is to improve crossbred performance under field conditions. Genomic selection (GS) using high-density genotyping could be used to address this. However in crossbred populations, 1) effects of SNPs may be breed specific, and 2) linkage disequilibrium may not be restricted to markers that are tightly linked to the QTL. In this study we apply GS to select for commercial crossbred performance and compare a model with breed-specific effects of SNP alleles (BSAM) to a model where SNP effects are assumed the same across breeds (ASGM). The impact of breed relatedness (generations since separation), size of the population used for training, and marker density were evaluated. Trait phenotype was controlled by 30 QTL and had a heritability of 0.30 for crossbred individuals. A Bayesian method (Bayes-B) was used to estimate the SNP effects in the crossbred training population and the accuracy of resulting GS breeding values for commercial crossbred performance was validated in the purebred population.

Results

Results demonstrate that crossbred data can be used to evaluate purebreds for commercial crossbred performance. Accuracies based on crossbred data were generally not much lower than accuracies based on pure breed data and almost identical when the breeds crossed were closely related breeds. The accuracy of both models (ASGM and BSAM) increased with marker density and size of the training data. Accuracies of both models also tended to decrease with increasing distance between breeds. However the effect of marker density, training data size and distance between breeds differed between the two models. BSAM only performed better than AGSM when the number of markers was small (500), the number of records used for training was large (4000), and when breeds were distantly related or unrelated.

Conclusion

In conclusion, GS can be conducted in crossbred population and models that fit breed-specific effects of SNP alleles may not be necessary, especially with high marker density. This opens great opportunities for genetic improvement of purebreds for performance of their crossbred descendents in the field, without the need to track pedigrees through the system.     

Mapping carcass and meat quality QTL on Sus Scrofa chromosome 2 in commercial finishing pigs

Quantitative trait loci (QTL) affecting carcass and meat quality located on SSC2 were identified using variance component methods. A large number of traits involved in meat and carcass quality was detected in a commercial crossbred population: 1855 pigs sired by 17 boars from a synthetic line, which where homozygous (A/A) for IGF2. Using combined linkage and linkage disequilibrium mapping (LDLA), several QTL significantly affecting loin muscle mass, ham weight and ham muscles (outer ham and knuckle ham) and meat quality traits, such as Minolta-L* and -b*, ultimate pH and Japanese colour score were detected. These results agreed well with previous QTL-studies involving SSC2. Since our study is carried out on crossbreds, different QTL may be segregating in the parental lines. To address this question, we compared models with a single QTL-variance component with models allowing for separate sire and dam QTL-variance components. The same QTL were identified using a single QTL variance component model compared to a model allowing for separate variances with minor differences with respect to QTL location. However, the variance component method made it possible to detect QTL segregating in the paternal line (e.g. HAMB), the maternal lines (e.g. Ham) or in both (e.g. pHu). Combining association and linkage information among haplotypes improved slightly the significance of the QTL compared to an analysis using linkage information only.     

<Emphasis Type="Italic">α</Emphasis>-Amylase inhibitor-1 gene from <Emphasis Type="Italic">Phaseolus vulgaris</Emphasis> expressed in <Emphasis Type="Italic">Coffea arabica</Emphasis>plants inhibits α-amylases from the coffee berry borer pest

Background  

Coffee is an important crop and is crucial to the economy of many developing countries, generating around US70 billion per year. There are 115 species in the < i > Coffea < /i > genus, but only two, < i > C. arabica < /i > and < i > C. canephora < /i > , are commercially cultivated. Coffee plants are attacked by many pathogens and insect-pests, which affect not only the production of coffee but also its grain quality, reducing the commercial value of the product. The main insect-pest, the coffee berry borer ( < i > Hypotheneumus hampei < /i > ), is responsible for worldwide annual losses of around US70 billion per year. There are 115 species in the Coffea genus, but only two, C. arabica and C. canephora, are commercially cultivated. Coffee plants are attacked by many pathogens and insect-pests, which affect not only the production of coffee but also its grain quality, reducing the commercial value of the product. The main insect-pest, the coffee berry borer (Hypotheneumus hampei), is responsible for worldwide annual losses of around US500 million. The coffee berry borer exclusively damages the coffee berries, and it is mainly controlled by organochlorine insecticides that are both toxic and carcinogenic. Unfortunately, natural resistance in the genus Coffea to H. hampei has not been documented. To overcome these problems, biotechnological strategies can be used to introduce an α-amylase inhibitor gene (α-AI1), which confers resistance against the coffee berry borer insect-pest, into C. arabica plants.