RNA:m5C-methyltranferases (MTases) Nop2 from S. cerevisiae and human proliferation-associated nucleolar antigen p120 are both members of a protein family called Nop2/NSUN/NOL1. Protein p120 is well-known as a tumor marker which is over-expressed in various cancer tissues. Using a combination of RNA bisulfite sequencing and HPLC-MS/MS analysis, we demonstrated here that p120 displays an RNA:m5C- MTase activity, which restores m5C formation at position 2870 in domain V of 25S rRNA in a nop2Δ yeast strain. We also confirm that yeast proteins Nop2p and Rcm1p catalyze the formation of m5C in domains V and IV, respectively. In addition, we do not find any evidence of m5C residues in yeast 18S rRNA. We also performed functional complementation of Nop2-deficient yeasts by human p120 and studied the importance of different sequence and structural domains of Nop2 and p120 for yeast growth and m5C-MTase activity. Chimeric protein formed by Nop2 and p120 fragments revealed the importance of Nop2 N-terminal domain for correct protein localization and its cellular function. We also validated that the presence of Nop2, rather than the m5C modification in rRNA itself, is required for pre-rRNA processing. Our results corroborate that Nop2 belongs to the large family of pre-ribosomal proteins and possesses two related functions in pre-rRNA processing: as an essential factor for cleavages and m5C:RNA:modification. These results support the notion of quality control during ribosome synthesis by such modification enzymes.Modified nucleotide 5-methylcytosine (m Post-transcriptional RNA modification is an integral part of global RNA maturation in all cell types. During this step, single enzymes or enzymatic systems form numerous chemically distinct modified residues. The great majority of RNA modifications are methylations, consisting of the transfer of a methyl group from S-adenosyl-L-methionine (SAM) to various positions in the base or 2'-OH of ribose .5C was first found in DNA, where it plays an essential role in epigenetic regulation ATP (3000 Ci/mmol) and purified on denaturing 8% polyacrylamide gels. Transcripts were incubated with 3 pmol of Nop2 or the N-terminal domain of Nop2 (1–220) in shift buffer  in 20 μL. The RNA/ protein complex was formed at 30°C for 10 minutes then incubated on Ni-NTA Sepharose beads washed with pull-down buffer  at room temperature for 10 minutes. Beads were washed three times for 5 min at room temperature with 1 mL of pull-down buffer supplemented with 1 mM DTT and 20 mM imidazole. Supernatant was discarded and beads were resuspended by vortexing in 5 μL of SBL . Samples were fractionated on 8% SDS-PAGE gels and analyzed by autoradiography. Experiment was repeated three times using different batches of transcripts and purified recombinant proteins.RNA bisulfite sequencing was performed as described in . In brie5C residues in ribosomal RNA by LC-UV-MS/MS was performed as described in . Un. Un5C-MTd medium . Nop2-denop2Δ diploid strain, a 2:2 spore distribution was obtained after sporulation, demonstrating the lethality of this deletion (nop2Δ did not restore growth (data not shown). Differences in amino acid sequence between NTDs of Nop2 and p120 could explain the growth defect of the nop2Δ expressing p120 strain. To understand the function of these different protein domains, we designed Nop2-p120 chimera protein. The NTD of Nop2 was linked to MTD and CTD of p120 to generate a hybrid protein (HYB)  . This ch0 itself . InteresΔNTD), indicating that localization of Nop2 is important for its function. To investigate the importance of this domain for Nop2 subcellular localization, we generated a new truncated mutant of Nop2. Alignment of p120 and Nop2 sequences revealed a small conserved region upstream of the MT domain ([221–383] of Nop2). Therefore, the first 220 amino acid residues were removed from Nop2 (Nop2Δ(1–220)). Strains expressing Nop2Δ(1–220) were viable, but exhibited a significant growth defect , as well as the HYB protein in a WT yeast strain. WT Nop2 protein was strongly enriched in the nucleus and concentrated in the nucleolus as shown by colocalization with the mRFP-tagged nucleolar marker Nop56 (Sik1) [S. cerevisiae strongly accumulated in the nucleolus.The NTD of Nop2 contains predicted subcellular sorting signals  44]. Ye. Ye44]. 6 (Sik1) . ResultsIn contrast, the HYB protein, which is composed of N-terminal Nop2 and C-terminal p120 domains, efficiently co-localized with mRFP-Nop56 within the nucleolus, demonstrating that all necessary cell sorting signals are indeed located in the Nop2 N-terminal domain.Yeast Nop2 was reported to be involved in the processing of the 35S rRNA precursor , 52 and 6-tagged-Nop2 and His6-tagged-Nop2 [1–220] immobilized on Ni-NTA Sepharose beads. As two m5C residues were recently identified in domain IV and V of rRNA 25S  domain, indicating that this positively charged domain is sufficient to mediate RNA binding. Taken together, these results show that the NTD domain of Nop2 is involved in specific RNA binding.The NTD from human p120 contains an arginine-rich domain that tightly binds to ribosomal RNA . It was rRNA 25S , both do5C residues at positions 2278 and 2870 and that the enzymes catalyzing these modifications are Rcm1 and Nop2, respectively  in bold characters and NoLS[99–110] is boxed [34]) are shown for p120. NLS which was suggested to drive Nop2 to the nucleus is shown in bold ((EPS)Click here for additional data file.S2 Fig(EPS)Click here for additional data file.S3 Fig(EPS)Click here for additional data file.S1 Text(DOC)Click here for additional data file.


Central to the InterPro database are predictive models, known as signatures, from a range of different protein family databases that have different biological focuses and use different methodological approaches to classify protein families and domains. InterPro integrates these signatures, capitalizing on the respective strengths of the individual databases, to produce a powerful protein classification resource. Here, we report on the status of InterPro as it enters its 15th year of operation, and give an overview of new developments with the database and its associated Web interfaces and software. In particular, the new domain architecture search tool is described and the process of mapping of Gene Ontology terms to InterPro is outlined. We also discuss the challenges faced by the resource given the explosive growth in sequence data in recent years. InterPro (version 48.0) contains 36 766 member database signatures integrated into 26 238 InterPro entries, an increase of over 3993 entries (5081 signatures), since 2012.The InterPro database ( InterPro was originally launched in beta in October 1999, with a full version 1.0 release in March the following year. From an initial core of four source databases  (iProtKB) , until nSignature integration: At InterPro, the matches between the latest version of UniProtKB and the new signatures  are determined and manually inspected by curators to ensure that they are accurate. Aberrant signatures, both old and new, that generate false positive matches are identified and reported back to the member databases. The new signatures passing quality control are added to InterPro. Each InterPro entry is annotated with a name, a descriptive abstract and GO terms. Hierarchical relationships are identified between the entries, tracing those entries that represent smaller, functionally specific subfamilies of larger families, or specific subclasses of broader classes of domain , which is part of the wider family of methionyl/leucyl tRNA synthetases. InterPro also predicts the protein to have a Rossmann fold, the two halves of which (shown in InterPro as two domains) are linked by a zinc-binding connective peptide domain. Two further domains are predicted—an anti-codon binding domain and a C-terminal domain. InterPro identifies these domains as subclasses of broader classes of domain, as indicated in the domain hierarchy annotation . Finally, towards the N-terminus of the protein, InterPro identifies a conserved site that is specific to class I aminoacyl–tRNA synthetases.Figure The data used to generate the summary were drawn from 16 individual signatures from seven member databases, as illustrated in Figure New database entries continue to be integrated into InterPro, and there have been 14 public releases since the last update (release 34.0 in 2012 ), with aThese increases are set against a constant background of flux in InterPro's member databases. The number of entries provided by each resource since 2007 (when InterPro began collating these data) is shown in Figure The percentage of entries integrated into InterPro for each member database is shown in Table The GO provides a controlled vocabulary that can be used to describe gene products in terms of their molecular functions, biological processes and the subcellular location in which they are found, in a consistent and structured fashion. InterPro entries are manually annotated with these terms, allowing GO terms to be inferred for sequences that match the entries, as part of the InterPro2GO pipeline. To date, over 11 500 InterPro entries have been annotated with one or more GO terms, with over 28 000 GO terms in total mapped to the resource. InterPro continues to be a considerable source of GO term annotation: GO terms assigned by InterPro2GO are cross-referenced more than 168 million times in UniProtKB release 2014_07, providing terms for almost 50 million individual proteins.http://www.microme.eu) is a resource for bacterial metabolism that aims to support the large-scale inference of biochemical pathways directly from genome sequence. To this end, Microme has developed a Genome-Reaction Matrix (GRM) containing inferred reactions from thousands of genomes that can be used to build draft metabolic networks and models. Several sources are used for the reaction sets, including InterPro annotations and GO terms, and curated associations of GO functions to reactions in the RhEA database , the number of genome-reaction associations by 9% , and the average number of reactions per genome also by 9% .The improved annotations were also propagated to UniProtKB, through the InterPro2GO pipeline, resulting in improved annotations for over 2.5 million sequences, as of release 2014_07. As an additional beneficial outcome, 35 new GO terms were created as part of this work, 74 new reactions were curated into RhEA ; this allows the InterPro database to be searched with a particular domain, or set of domains, returning all of the domain architectures and associated proteins that match the query. This makes it easy to rapidly identify all of the different domain combinations, where one type of domain co-occurs with another, or where a particular domain is followed by another domain , and to list all of the proteins in UniProtKB with a matching domain architecture.A new domain architecture search tool has been developed and made available via the website  are not catered for, since such entries tend to be near full length and typically do not undergo recombination.The tool is specifically designed to work with InterPro entries of type The tool makes use of a specialized graph-theory-based algorithm that rapidly searches through all domain matches within InterPro and returns proteins that match the domains in the order specified in the query. As InterPro integrates data from a number of different member databases whose domain boundary predictions do not always agree, InterPro domains may overlap. This is in contrast to the ‘beads on a string’ representation that is sometimes used to display domain architectures.Users can launch the tool using an interactive panel on the left-hand side of the page. Clicking on this launches a pop-up window with a searchable list of all of the domains in the database ; (ii) programmatically via Web services that allow up to 25 sequences to be analysed per request (SOAP-based service documented at http://www.ebi.ac.uk/Tools/webservices/services/pfa/iprscan5_soap and REST-based service at http://www.ebi.ac.uk/Tools/webservices/services/pfa/iprscan5_rest) and (iii) as a downloadable package for local installation (https://code.google.com/p/interproscan/wiki/Introduction).The InterPro database and related software are freely available for download and distribution, provided the appropriate Copyright notice is supplied (as described in the accompanying Release Notes). Data can be downloaded in a flat-file format (XML) and via the Web interfaces described in the text. The InterProScan software is available: (i) as a browser-based tool for analysing single protein sequences  methodologies. As a consequence, the rate of deposition of nucleotide (and thus protein) sequence data has greatly increased: at the beginning of this century, UniProtKB contained ∼470 000 entries; the current total is ∼80 million, ∼40 million of which were added in the last year alone.week, and the rate of sequence deposition is growing.A key challenge facing bioinformatics is the accurate and consistent annotation of these sequences. The scale of this task is illustrated in Figure Clearly, even the most extensive manual efforts cannot meet the challenge of annotating these data. Automated annotation transfer is also beyond the scope of all-against-all pairwise-alignment methods, such as BLAST, due to the sheer scale of the task. Given this, InterPro with its scalable, signature-based approach is more important than ever in providing annotation. The resource has not only managed to keep track with the massive growth of UniProtKB in recent years, but has actually increased its coverage (from 79.6% of proteins in the database in 2011 to 83.5% in 2014). This is owing to a number of factors: the on-going development of new signatures by its partner databases  by an expert curator generated a cumulative ‘snowball’ effect, improving annotation for over 2 million of UniProtKB sequences, with positive knock-on effects on a host of other resources . We are very interested in exploring similar collaborations in future, as this approach potentially allows us to rapidly  improve annotation of proteins that may not be adequately covered in UniProtKB at present.Scalable provision of automatic annotation is important not only for UniProt, but also for other areas of informatics, and improvements in InterPro feed through into other resources. For example, the increased coverage, performance and improved annotation of microbial proteins involved in transport and metabolism will feed into EBI Metagenomics , a recen


E. coli, B. pertussis, and P. aeruginosa, as well as other animal and plant pathogens. The serralysin proteases are structurally dynamic and their folding is regulated by calcium binding to a C-terminal domain that defines the RTX family of proteins. Previous studies have suggested that interactions between N-terminal sequences and this C-terminal domain are important for the high thermal and chemical stabilities of the RTX proteases. Extending from this, stabilization of these interactions in the native structure may lead to hyperstabilization of the folded protein. To test this hypothesis, cysteine pairs were introduced into the N-terminal helix and the RTX domain and protease folding and activity were assessed. Under stringent pH and temperature conditions, the disulfide-bonded mutant showed increased protease activity and stability. This activity was dependent on the redox environment of the refolding reaction and could be blocked by selective modification of the cysteine residues before protease refolding. These data demonstrate that the thermal and chemical stability of these proteases is, in part, mediated by binding between the RTX domain and the N-terminal helix and demonstrate that stabilization of this interaction can further stabilize the active protease, leading to additional pH and thermal tolerance.The serralysin family of bacterial metalloproteases is associated with virulence in multiple modes of infection. These extracellular proteases are members of the Repeats-in-ToXin (RTX) family of toxins and virulence factors, which mediated virulence in  Serratia marcescens is an opportunistic human pathogen associated with multiple modes of infection, including pneumonia, empyema, urinary tract infection, corneal keratitis, meningitis, endocarditis, and septic arthritis., the binding isotherms appeared sigmoidal. Below 10 μM Ca2+, intrinsic fluorescence was low and did not vary with changes in Ca2+ concentration. Between 10 and 200 μM [Ca2+], fluorescence increased and appeared to saturate between 100–200 μM [Ca2+] . A small population of the protein also eluted in the void and likely contained aggregates of the RTX protein. The Ca2+-bound protein was similarly injected onto a column that was pre-equilibrated with 2 mM Ca2+. In the presence of Ca2+, the RTX domain eluted at approximately 14.7 mls (closed circles). Neither peak showed significant signs of tailing or asymmetry. The shift in elution volume was consistent with a disordered and extended RTX polypeptide in the absence of Ca2+ and a compact, folded RTX domain in the presence of 2 mM Ca2+. Based on known gel filtration standards, the hydrodynamic radius of the Ca2+ bound protein was in close agreement with the predicted molecular mass of roughly 25 kDa.The structural changes associated with Ca2+-induced folding of the full-length PrtS protein, recombinant PrtS was purified under denaturing conditions and refolded in vitro. Protein solubility and monodispersity were utilized to assess the structural changes associated with Ca2+ binding, as previously described.. Densitometric analyses of the western blots confirmed a cooperative Ca2+ dependence of PrtS refolding with an apparent affinity of 27 ± 11 μM with a Hill coefficient of 1.7 ± 0.4  were tested using the activity assay. Endpoint fluorescence after incubation in the presence of 2 mM divalent cations was used to assess their ability to fold and activate the protease .,14,29 Tonditions . When no2+ and the refolded protease was subsequently incubated at the indicated temperatures in the presence of the fluorescent substrate. After equilibration for 10 minutes at reaction temperatures, the peptide was added and the digests proceeded for 10 minutes before being quenched with EDTA. Endpoint fluorescence of the cleaved peptide was then measured  were assessed for their conservation and their potential interactions with Arg302 and Val339. Multiple sequence analyses indicated that many sites showed sequence variation within this amphipathic helix and suggested that substitutions might be tolerated at positions Ala8 and Leu12 .32] Ana Ana32] ABased on the sequence and structural analyses, a series of cysteine substitutions were selected to assess whether stabilization of this domain-domain interaction could be used to further stabilize the protease. Paired cysteine substitutions at positions A8C-V339C and L12C-R302C were introduced by site directed mutagenesis . The effThe proteases were first refolded then diluted into reaction buffers at the indicated temperatures. Activity was first assessed under relaxed conditions where the wildtype protein showed high activity: pH 7.5 and 55°C. In the presence of DTT, small changes in PrtS activity could be seen using the fluorescent peptide substrates . The mutTo further evaluate how changes in protease activity relate to putative disulfide formation, the denatured proteases were incubated in maleimide to specifically label the engineered cysteine residues. Based on previous work, the disruption of the helix-RTX domain packing by the maleimide-labeled cysteines would be predicted to decrease protease stability and activity at elevated temperatures and would mimic substitutions in the RTX-helical interface seen in AprA.  The maleTo further evaluate the effects of putative disulfides, more restrictive reaction conditions, pH 9.5 and 55°C, were selected based on the pH and temperature activity profiles . Again, In contrast, refolding in the presence of disulfide-promoting additives increased protease activity in the restrictive conditions when compared to wildtype . The A8C2+ binding. In  In P. aeSimilar to many other bacterial exoproteases, PrtS exhibits high stability with robust protease activity across a wide range of temperatures and pHs . The evo2) and, when disrupted, cause a loss in protease stability. As a result, the Ca2+ regulated AprA RTX folding is critical for two events: the nucleation of protease domain folding and its activation and the formation of the helical saddle that provides for protease stability. In the absence of the N-terminal helix or disruption of its packing to the RTX domain, protease stability and activity are severely compromised. Coupling these two functions to RTX folding is likely beneficial for protease secretion, which is thought to require an unfolded and extended polypeptide.[2+ of the intracellular environment, the protease remains unfolded. Only after being secreted in a Ca2+-rich environment does the protease adopt native structure. Once in the native state, the N- and C-terminal structures are competent to bind and stabilize the folded form.Previous studies with AprA demonstrate that, once folded, the saddle of the folded RTX β-helix bound the N-terminal helix.,13,18 Thypeptide.,38 In thBuilding on this model, the introduction of cysteine pairs resulted in the hyper-stabilization of the PrtS protease in a disulfide-dependent fashion Figs –6. The iThese data provide additional evidence for the physical basis of RTX protease stability and suggest means by which these activities could be modulated for a variety of purposes. Disruption of the RTX-N-terminal helix interaction may provide a mechanism to down-regulate protease stability and, in turn, activity. Such an approach might be useful in designing modulators to decrease the activity of these virulence factors therapeutically. In contrast, stabilization of this interaction provides a means to up-regulate protease stability and activity and may be useful for industrial applications wherein enzymatic function is required at elevated temperatures, non-neutral pHs or under harsh conditions.


Cell]).Protein kinases control cellular responses to environmental cues by swift and accurate signal processing. Breakdowns in this high-fidelity capability are a driving force in cancer and other diseases. Thus, our limited understanding of which amino acids in the kinase domain encode substrate specificity, the so-called determinants of specificity (DoS), constitutes a major obstacle in cancer signaling. Here, we systematically discover several DoS and experimentally validate three of them, named the αC1, αC3, and APE-7 residues. We demonstrate that DoS form sparse networks of non-conserved residues spanning distant regions. Our results reveal a likely role for inter-residue allostery in specificity and an evolutionary decoupling of kinase activity and specificity, which appear loaded on independent groups of residues. Finally, we uncover similar properties driving SH2 domain specificity and demonstrate how the identification of DoS can be utilized to elucidate a greater understanding of the role of signaling networks in cancer (  •Residues driving specificity in the kinase and SH2 domains are globally identified•Three new such residues, termed αC1, αC3, and APE-7, are experimentally validated•Specificity and catalytic activity appear to be encoded in distinct sets of residues•The global identification of determinants allows the modeling of rewiring mutations Determining the residues that drive the specificity of kinases and of SH2 domains that bind phosphorylation sites paves the way for a systematic interpretation of mutations on signaling networks. Cellular organization and response to external and internal cues relies on swift and precise processing of information through cell signaling networks. High fidelity in these circuits depends critically on the recognition and phosphorylation of specific substrates by protein kinases, and perturbations of this cellular system have been linked to significant evolutionary transitions , as wellCellular signaling fidelity is maintained essentially through two coupled mechanisms. At a macro-molecular level, protein specificity ensures that each protein kinase will reach and interact with its protein substrates. At a micro-molecular or atomic level, peptide specificity defines the ability of a given kinase domain present in all active protein kinases to recognize and phosphorylate a specific peptide within the protein substrate  Figure A. A variHere, we present a computational approach that aims to overcome these limitations and address the following open questions. Which residues within the kinase domain contribute to peptide specificity ? Are these determinants just a small group of residues localized in close proximity to the substrate as currently thought, or do they form a sparse network of residues instead C? Are suCell]), which explores how cancer mutations affect domain specificity by integrating the DoS identified here, resolving these questions could represent a valuable contribution not only for basic signaling biology but also for cancer research.As we demonstrate in our accompanying article  explores the possibility that within a large ensemble of specificity masks, certain masks can discriminate between kinases with dissimilar substrate specificities better than others. These masks will range from those capturing very few and localized DoS  for each kinase are predicted by comparing all kinases across the human kinome at each amino acid position within the kinase domain (amino acid similarity) and by incorporating a weighting factor  of the “specificity importance” of each position as determined by the given specificity mask. A PSSM for each kinase is then predicted by integrating the PSSMs for the other kinases using the mask-dependent similarity as a weighting factor. Naturally, the majority of masks within the original set of random masks will predict specificity poorly, but, as the system evolves, the masks will improve their predictive power, i.e., become more fit.Second, masks are ranked according to their predictive performance . In essence, masks that more closely capture the true contribution of each position within the kinase domain  will result in a better prediction of the specificity profiles, thus ranking higher.Third, the worst-performing masks are filtered out and new masks, representing both subtle (mutation) but also more abrupt (cross-over) variations of the best-performing masks, will be added.These three steps are initially started with random specificity masks and repeated until convergence is reached and fitness cannot be optimized further. Residues consistently scoring higher in the specificity masks following the optimization procedure will be considered candidate DoS. For a more technical description of the algorithm, please refer to Since our method contains stochastic aspects (such as the starting set of random masks and the generation of new masks by mutation and cross-over), one initial question that must be addressed is whether the method is robust to this initial stochasticity, i.e., whether one would obtain similar results if the process was started with arbitrary initial conditions and evaluated independently several times. To this end, we compared the fitness evolution of ten independent KINspect evaluations and found highly comparable fitness trajectories, as well as increasing similarity between the best-performing masks at each generation , and S3.Moreover, we also explored a vast number of possible combinations of residues and specificity models. Since convergence in the model requires approximately 2,500 cycles of the above three steps (in the case of the human kinase domain) and 100 specificity masks are used at every generation, 250,000 models were explored in the kinome-wide search for the most informative masks. By repeating this algorithmic deployment independently ten times with arbitrary initial conditions, 2,500,000 models were explored in total. The high number of models explored and the fact that the independent evaluations converge on their solutions imparted confidence that the results obtained could be close to the “true mask” of specificity.−7).In order to further benchmark our approach, we collected an inclusive “golden list” of residues that had been suggested or predicted as DoS  in the lIn addition to identifying candidate DoS, our approach can predict the domain specificity (PSSM) of every kinase in the human kinome from sequence alone. Therefore, we could compare these to those kinases where the specificity profile has previously been experimentally determined  and asseWhile the results in We next selected a group of residues predicted by KINspect to be DoS and devised PSPL experiments to experimentally validate their involvement in specificity. In particular, as shown in For our second experiment, we selected a position (named APE-7 as it is located seven residues before the APE motif delimiting the activation segment) with a score of 0.75 in close proximity to residue P+1 B. SimilaTaken together, these results demonstrate that KINspect successfully identified a set of residues on which the specificity of the entire domain is encoded.In order to evaluate the relationship between the different DoS, as well as between the DoS and the peptide substrate, we investigated their spatial distribution in the kinase domain. First, we note that several of the determinants localize relatively far from the peptide substrate. However, most of these distant DoS seem coupled to other DoS through “canals”  that eventually contact the substrate peptide, as shown, for instance, in Second, closer inspection of the results  suggestsWe next set out to explore whether evolutionary insights could be derived from these results. It has previously been observed that the evolution of the kinase domain as a whole is not an accurate reflection of how different kinases have evolved different peptide specificities . Thus, wThus, this analysis provides further proof and explanation as to how and why the evolution of the entire domain does not always parallel specificity evolution . Using tWith the aim of interpreting our results from a more global perspective, we investigated to what extent the DoS residues identified by KINspect can interplay with residues known to be involved in the catalytic activation and regulation of the kinase domain.Two independent sets of residues playing such crucial roles have been identified forming hydrophobic interactions at the core of the domain and stabilizing the active conformation of the domain . These tDespite this apparent separation of biological functions in the kinase domain, it is at the same time equally important to highlight that KINspect, in agreement with previous observations , identifTo investigate the generality of these observations, we explored DoS patterns in another signaling modular protein domain, namely, the SH2 domain. Following a very similar approach as described for the kinase domain, and after identifying the required parameters  appropriBeing a smaller domain of typically approximately 100 residues . Here, we developed a data-driven systematic approach to investigate the presence of DoS residues throughout the human kinome, experimentally validated several of these DoS, which together with those shown in the accompanying article  encode sThe sparse networks of DoS also present interesting implications when compared and contrasted with previous work.First, as mentioned earlier and illustrated in Moreover, this separation of function, together with our finding of very different evolutionary speeds and trajectories for spines and DoS, makes us speculate that kinases have evolved within tight constraints around spines, where maintaining spine integrity was critical to retain kinase activity. On the other hand, the more loose constraints on DoS have facilitated the evolution of new kinases with distinct specificities, a view that is consistent with the current understanding of the evolution of signaling systems .Furthermore, the picture portrayed by our results of sparse networks of multiple residues driving specificity together would fit within the scope of more recent theories on protein function, namely, the so-called protein sector model. According to this model, protein function is often encoded in protein sectors, defined as subsets of co-evolving residues  identifiDespite the significant conceptual and analytical leap forward provided by KINspect in terms of capability and coverage, continued experimental and computational advances will make it even more precise and accurate in the future.From an experimental perspective, it is clear that obtaining peptide specificity profiles for a larger number of kinases  will only improve our method’s results.In terms of extending to other applications and expanding our current approach, KINspect's methodology could potentially be applied to several other fundamental biological questions such as the identification of residues driving kinase inhibitor binding and specificity. Naturally, we also plan to expand KINspect to add new peptide-recognizing modular domains other than the already-included kinase and SH2 domains  or even include inter-positional dependencies within the substrate peptide in the future when data become available.As introduced earlier, peptide specificity is a crucial component of a wider cellular requirement, signal fidelity, which ensures that cells will correctly decode input cues and respond accordingly. Changes in this system have been identified as playing a critical role in multicellular metazoan evolution , but alsThe learning classifier system briefly described in the main text that constitutes the computational engine behind KINspect is illustrated in As a measure of dissimilarity between matrices or vectors, the Frobenius distance or norm can be simply calculated as the square root of the difference between every value in the two matrices or vectors squared .http://kinase.com/ repository, with more recent and up-to-date unpublished data kindly provided by Dr. Gerard Manning . Peptide library analysis was performed by arraying a set of 182 peptide mixtures (50 μM) in a 1,536-well plate in kinase reaction buffer (2 μl/well). Buffer for Pim1 reactions was 50 mM HEPES (pH 7.4), 10 mM MgCl2, 0.1% Tween 20, and buffer for PKCγ reactions was 50 mM Tris-HCl (pH 7.5), 10 mM MgCl2, 1 mM DTT, 0.1% Tween 20 containing a 5-fold dilution of lipid activator (EMD Millipore). Peptides had the sequence Y-A-X-X-X-X-X-S/T-X-X-X-X-A-G-K-K-biotin, in which X positions were generally an equimolar mixture of the 17 amino acids excluding Ser, Thr, and Cys, and S/T is an even mixture of Ser and Thr. In each well of the array, the peptide had one of the 20 amino acids fixed at one of the nine X positions. In addition, two peptides were included that fixed either Ser or Thr at the phosphoacceptor position. Reactions were initiated by adding kinase (to 8 μg/ml) and [γ−33P]ATP (50 μM at 0.03 μCi/μl), incubated 2 hr at 30°C, and then 200-nl aliquots were transferred to a streptavidin membrane (Promega). Membranes were washed and dried as described and exposed to a phosphor screen. Radiolabel incorporation into each peptide mixture was quantified by phosphor imaging using QuantityOne software (Bio-Rad). Following background subtraction, data were normalized so that the average value for a given position within the peptide was equal to 1. Normalized data from two (PKCγ) or three (Pim1) separate runs were averaged, log2 transformed, and converted to heatmaps in Microsoft Excel.PKCγ (WT and mutant) was produced in HEK293T cells with a 3 × FLAG epitope tag at the C terminus and isolated by affinity purification on M2 FLAG antibody resin (Sigma-Aldrich) as described . Pim1 (WP.C. and R.L. conceived the project. P.C., A.P., C.C.S., and M.N. developed and implemented the computational framework. P.C., C.J.M., H.J.L., and B.E.T. devised and/or performed experiments. P.C. and A.P. generated the structural visualizations with Chimera and performed the evolutionary analysis of DoS. R.L. oversaw the project. P.C. and R.L. wrote the article assisted by the other authors. All the authors read and approved the final manuscript.


However, there is a common and implicit g-factor view of creativity that potentially stems from the assumption that creativity represents an ability normally distributed in the human population , ranging from everyday manifestations to eminent accomplishments. Indeed, individual differences exist in the outcome of human creative potential , but this does not suggest that creativity represents a generalized entity per se. This nuance is critical since many psychological and neuropsychological studies of creativity have made inferences about creativity as a generalized construct while relying on a set of highly specific tasks within highly specific domains, although there is limited support for the domain-generality of creativity. In fact, rare eminent individuals are those associated with exceptional creative achievement in multiple domains, and across multiple subdomains within a given field  a domain-general ability, (2) a set of domain-specific abilities, and (3) a set of task-relevant abilities  of an individual's creative potential. This potential is differentiated because the individual has, voluntarily or not, specialized into a specific content area. With the emergence of domains of interest in which individuals focus their commitments, adolescence seems to be the critical time for the development of such “specialized” creative potential  for which we know there is limited evidence.Hence, it is possible that an adolescent committed to a specific creative outlet will strengthen the neurological substrates that underpin the resources critical for that particular outlet by “activating” them on a regular basis. Using the creative writing example, an adolescent who regularly creates poems will develop a set of task-relevant skills  that are associated with underlying neurological structures. Because writing poetry also “activates” a set of domain-specific skills , this adolescent will likely show creative potential not only in outlets that require a similar combination of task-relevant skills , but also, to some extent, in outlets that involve similar domain-specific skills . It is important to contrast this sort of specialization–differentiation hypothesis also finds support in several behavioral studies using training and transfer designs. They have shown that specific resources in one creativity domain can partly carryover in domains that share similar task-requirements (Baer, Domain-General factor, the contribution of such a factor may only be minimal.The ts Baer, . Developspecialization–differentiation hypothesis addresses current misconceptions of creativity as a domain-general and generalized entity. We propose that task-oriented commitment is an organizing principle of the creative potential. By specializing in creative domains and tasks of interest, a person's creative potential will progressively differentiate into task-relevant skills underlined by specific brain regions recruited on a regular basis. We posited that such process could peak during adolescence, given the neurobiological context associated with this period. Future longitudinal studies within the field of psychology and developmental neuroscience should explicitly test this hypothesis to uncover the developmental pathways leading to differentiated creative potentials in specific creativity outlets. To this end, work focusing on the neural systems underlying motivated behaviors (e.g., Ernst, In conclusion, the proposed The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


N = 40; 8th and 11th graders) was to gather salient characteristics of academic domains from students' perspective. In Study 2  the 13 characteristics identified in Study 1 were assessed along with academic emotions in four different domains  using a questionnaire-based trait assessment. With respect to the same domains, state emotions were assessed in Study 3  by employing an experience sampling approach. In line with our initial assumptions, between-domain relations of trait but not state academic emotions reflected between-domain relations of domain characteristics. Implications for research and practice are discussed.With the aim to deepen our understanding of the between-domain relations of academic emotions, a series of three studies was conducted. We theorized that between-domain relations of trait  emotions reflected students' judgments of domain similarities, whereas between-domain relations of state  emotions did not. This supposition was based on the accessibility model of emotional self-report, according to which individuals' beliefs tend to strongly impact trait, but not state emotions. The aim of Study 1 (interviews;  Empirical educational research has largely neglected the role of students' emotional experiences, with the exception of extensive research on test anxiety  are stronger than those associated with others . Goetz et al.  are almost entirely based on reports of habitually experienced academic emotions , whereas trait measures are thought to reflect individuals' beliefs about emotions . In other words, beliefs  are assumed to bias the assessment of trait emotions, whereas reports of real-time emotions in the “here and now” may be less impacted by such beliefs. A number of studies supports this model and shows that it is hardly possible to make conclusions about individuals' actual emotions experienced in real-life situations from their reports of habitual emotions  our aim was to identify characteristics of academic domains from students' perspectives. The results of this study were a prerequisite for our two subsequent investigations. In Study 2 (questionnaire study) we assessed the identified characteristics and emotional experiences  in different academic domains . We compared patterns of between-domain relations of trait academic emotions with those of domain characteristics and anticipated similar patterns for both constructs. For example, we theorized that mathematics and physics would be judged as being more similar in their characteristics than mathematics and English, and that this would be reflected in between-domain relations of academic emotions. More specifically, we hypothesized that there would be stronger relations between emotions experienced in mathematics and physics as compared to those experienced in mathematics and English. Finally, we examined between-domain relations in real-time academic emotions  and predicted that the pattern of between-domain relations of real-time (state) emotions would show a weaker association with the pattern of between-domain characteristics as compared to trait emotions. This hypothesis was based on the assumption that domain characteristics should be more salient in reports of trait as compared to state emotions. In each of the three studies discussed, two samples of differing age groups were assessed (8th and 11th graders) to provide an indicator of how strongly generalizable results were with respect to students' age. In sum, this research comprises three studies that intend to offer a rather comprehensive picture on how between-domain associations of academic emotions reflect judgments of academic domain characteristics.The procedure was in compliance with the ethical standards  and was deemed appropriate by the Institutional Review Board of the University of Konstanz. Participation was voluntary. Written informed consent was obtained from all participants. Furthermore, parents of study participants were informed about the nature of the study and its procedure, and the heads of schools as well as teachers who taught in the classes investigated approved the study protocol. Once the data were collected and entered, all identifiers that could link individual participants to their results were removed and destroyed. Hence, all the analyses were conducted on depersonalized data.Different lines of research  have tackled the question of what actually constitutes an academic domain. However, each of these lines of inquiry is restricted to a very specific perspective. Further, previous studies that examined students' views on domain characteristics used categories that were predefined by experts  and 11th (N = 20) graders  from four different German high schools. The average age of participants was 15.79 years . Participation was completely voluntary and data collection was anonymous.The study sample included 8th  mathematics, (2) physics, (3) German, (4) English, (5) biology, (6) history, and (7) music. We used single items to keep the length of the interview reasonable as students were asked to answer the question about multiple domains. Students were encouraged to list as many characteristics as they wanted within each domain. If students did not understand the exact wording of the question, or referred to things not related to the question, the interviewer focused the student on characteristics of the subject domains. These probes were intended to help students to focus on the main question without directing their attention to specific characteristics of the domain. Prompts were offered when students deviated into generalities (“Please try to name only the concrete characteristics of the domain”), if students talked about their feelings , or if students talked about the content of a given subject . All interviews were audio recorded and transcribed.Interviews were conducted by trained research personnel and each student interview lasted approximately 10 min. Students were asked the following question, repeated for each of the seven academic domains: “Qualitative content analysis was used  and non-quantified statements were valued identically. This procedure resulted in determining the percentage of participants who contributed at least one statement to a specific category. Ambiguous or incoherent statements that did not refer to the question were not included in the results section.quantity of the material that students are confronted with in a domain, (2) difficulty of the content to be learned in a domain, (3) variety of the content, the heterogeneity of the content taught in a domain, (4) coherence of the content, how strongly different topics in a domain are related to each other, (5) amount of illustration in how the material is taught, (6) relations to everyday life, to what amount are topics taught in a domain related to students' out of school life , (7) amount of up-to-date-topics, how many of the topics taught in the subject refer to topics currently discussed by students and in society, (8) indisputability of correct task solutions, the degree to which the correct task solutions are clearly defined, (9) exchange of views among students, the degree to which a domain affords students the possibility of exchanging views and thoughts, (10) wearisomeness, how physically and mentally tiring and demanding the study is within a subject, (11) talent necessary for good grades, how important it is to be talented in a domain in order got get good grades, (12) value of achievement, how important it is to get good grades in a domain, and finally (13) value independent of achievement, how important a domain is to a student independent of the achievement level reached within this domain. For each of the 13 categories an example of a student statement is presented in Table Based on qualitative content analyses Mayring,  altogethhoughts, 0 wearisoRelative frequencies of all 13 categories are shown in Figure the degree of subject definition as outlined by professionals; Stodolsky, Thirteen academic domain characteristics were identified based on students' statements gathered in interviews. Although all of the 13 characteristics derived from Study 1 have been mentioned in previous studies (in some cases with different names), the current results revealed categories that were salient to students . Students participated in this study on a voluntary basis, and were tested in their regular classrooms settings. The data were collected by trained testing personnel via a self-report instrument (questionnaire). It took students, on average, 25 min to complete the questionnaire. Eighth-graders have an average of 3/2/4/3 academic hours of mathematics/physics/German/English, and eleventh-graders have an average of 4/3/4/4 academic hours in those domains.The sample consisted of 855 8th and 854 11th graders  from 74 classes (35/39 in grade 8/11) from 11 different German high schools. The average age of participants was 15.95 years ; however, in previous and comparable studies, reliability of single-items was demonstrated, for example, by correlating it with full scales  to 5 (very strongly). The order of the items was as follows: Enjoyment with respect to (a) mathematics, (b) English, (c) physics, (d) German, followed by anger, pride, anxiety, and boredom with respect to the four domains, in the same order.llegen'S  circumplllegen'S . After cCalculating similarity indices s(d)s. The two-level structure of the data with students  nested within classes  was taken into account when analyzing the data using Mplus 5.2 software s that are based on building mean levels of z-standardized correlation coefficients -values (both with respect to domain characteristics and academic emotions) indicate the strength of between-domain relations for each domain pair and can be interpreted in terms of effect sizes  mean correlations were re-Fisher-z-standardized, resulting in the six s(d)-values (mean correlations) for each grade levelIn a first step, for each domain pair  values of academic characteristics related to the two domains were correlated. As a result, for six domain pairings (based on four academic subjects) 13 (number of characteristics) correlations were calculated, yielding altogether 78 correlations for each grade level. In a second step, all of the correlations were Fisher-s(d)s for academic emotions were calculated. The six s(d)-values of academic emotions referring to the domain pairs were based on altogether 30 correlations (5 emotion × 6 domain combinations) for each grade level. Thus, for both characteristics of domains and academic emotions s(d)-values show how strongly these constructs are related with respect to two domains (domain pairs). The important feature of the s(d)-values is that they can directly be compared across domain pairs  and constructs (domain-characteristics vs. emotions).In a similar way, Comparing s(d)s-matrices. The six s(d)-values were presented in a matrix both with respect to domain characteristics (matrix A) and emotions (matrix B). Based on the residual matrix [representing difference scores on the corresponding six s(d)-values in matrices A and B] the SRMR  was calculated to estimate whether the two matrices differ from each other , and σij the elements of matrix Σ ; p denotes the number of variables, on which the two matrices are based . In this expression, ijs and σij refer to covariances as represented in the two matrices. However, due to the fact that in the matrices of the present study the s(d)-values reflect correlations, the RMR as calculated above reflects the SRMR. According to Hu and Bentler s for domain characteristics and academic emotions -values as outlined in Table With respect to the research question, Table s(d) = 0.31], followed by the German/English domain pair (0.26) and finally, all other domain combinations (0.08 ≤ s(d) ≤ 0.15). This pattern parallels the between-domain relations found for academic emotions, in which the strongest effects were also found for mathematics/physics domain pair [s(d) = 0.41], followed by the German/English domain pair (0.34) and finally all other domain combinations [0.15 ≤ s(d) ≤ 0.19]. In order to statistically test this apparent similarity between the two matrices, we calculated the SRMR. The comparison of matrices revealed the SRMR of 0.05 which is below the cutoff value of 0.08  = 0.46] and the German/English (0.24) domain pairs, followed by all other domain combinations [0.07 ≤ s(d) ≤ 0.10]. This pattern is similar to the between-domain relations found for academic emotions, in which the strongest effects were also revealed for mathematics/physics [s(d) = 0.55], and the German/English (0.24) domain pairs, followed by all other domain combinations [0.09 ≤ s(d) ≤ 0.10]. The comparison of matrices revealed the SRMR of 0.03 for which is below the cutoff value of 0.08  of academic emotions  than reports of habitual, or trait, emotions . From each of the 41 classes, two to four students were randomly selected to participate in the study. All participants took part in this study on a voluntary basis.The sample consisted of 58 8th and 63 11th graders  from 41 classes (21/20 in grade 8/11) from 11 different German high schools. The average age of participants was 15.96 years . On average, 3.60, 2.50, 3.35, and 3.16 of the questionnaires were related to mathematics, physics, German, and English, respectively.Data were collected using the experience sampling method  to 5 (very strongly).To avoid overly intrusive questionnaires, state constructs were assessed using single-item measures. This practice is consistent with findings from Wanous et al.  indicatis(d)s were calculated by employing the procedure delineated in Study 2 -values indicate the strength of between-domain relations of academic emotions for each domain pair, and can be interpreted in terms of effect sizes s-values for state emotions was compared with the matrix containing the s(d)s-values for domain characteristics (derived in Study 2).To analyze the strength of between-domain relations of state academic emotions, similarity indices Means and standard deviations of constructs are outlined in Table s(d)-values (similarity indices) were rather consistent for both age groups . The pattern of relations did not consistently show stronger between-domain associations for the mathematics/physics and German/English domain pairs as compared to other possible domain combinations. In terms of effect sizes [s(d)-values], all relations were weak to medium.With respect to the research question, Table s(d)-values for state academic emotions with those of domain characteristics (from Study 2), the revealed SRMR was 0.09 for both the 8th and the 11th grade. These values were clearly higher than those found in Study 2 (trait emotions) indicating that the matrices were reasonably different from each other. Even more important is the fact that the differences were stronger in Study 3 as compared to Study 2. In sum, the between-domain relations of trait academic emotions more strongly reflect interrelations of domains with respect to students' judgments of domain characteristics, as compared to assessment of state, or real-time, academic emotional experiences.When comparing all s(d) related to mathematics/physics and s(d) related to mathematics/German were 0.16/0.37 for the trait assessment and 01/0.07 for the state assessment for grade levels 8/11. Although differences in s(d) in the trait assessment strongly reflected the difference in s(d) related to the judgments of domains (0.25/0.45 for grade levels 8/11), the differences in s(d) in the state assessment did not.Although the trait assessment revealed that the domain pairs of mathematics/physics and German/English were judged as being more similar than other pairs (both with respect to domain characteristics and academic emotions), this pattern was not found in the state assessment of academic emotions. For example, in terms of effect sizes, the differences in similarity indices It is important to note that the data of Study 2 and 3 were not assessed with the same sample. However, both studies included two sub-samples (8th and 11th graders) and the results across age groups were very similar, all of which provides strong support of study hypotheses.The aim of the present research was to contribute to the existing knowledge regarding the pattern of between-domain relations of students' academic emotions. Previous research has shown that between-domain relations of trait academic emotions strongly differ with respect to the domain pairs under investigation. The focus of the present study was to contribute to our understanding of why such patterns of between-domain relations of trait academic emotions arise.One of the main goals of the current study was to investigate whether the pattern of between-domain relations in trait academic emotions reflected similarities and dissimilarities of academic subject domains as perceived by students. To accomplish this goal, students' perspectives on the most salient characteristics of academic domains were gathered (Study 1). Thirteen main characteristics were identified from student interviews, including the difficulty of content, the value of achievement, and the amount of illustration of the material. From a practical perspective, these categories may assist educators in understanding what aspects students focus on when thinking about subject domains.To further address the main aims of this research, thirteen characteristics identified in Study 1 were assessed in combination with the assessment of five trait academic emotions  in the four subject domains of mathematics, physics, German, and English . Consistently with the study hypothesis, rather similar patterns for between-domain relations of domain characteristics on the one side and academic domains on the other side were revealed. According to the assumptions that cognitions about domains are first of all salient in trait assessments, we presumed that similar patterns for between-domain relations of domain characteristics and academic emotions would be detected in trait but not in state assessments of academic emotions. To this end, between-domain relations of real-time emotions were examined .In line with this assumption, Study 3 indicated that the pattern of between-domain relations of state emotions did not reflect the pattern of between-domain relations of domain characteristics. In sum, the two main studies herein reported  showed that the between-domain structure of academic emotions (trait) reflects the structure of cognitive domain judgments, whereas real-time emotions (state) do not, thus supporting previous research.feeling more similar in those domains. This supports previous reports in the literature showing that trait emotions more strongly reflect what we think about our feeling, and not just what we really feel  may be more important than what we really feel. Thus, both trait and state emotions matter, and it might be misleading to suggest that one approach would be “better” than the other. It is advisable, however, that researchers and practitioners alike bear in mind the fact that state and trait reports on academic emotions represent different conceptual entities.The studies herein reported demonstrated that the degree of similarity between the pattern of between-domain relations of domain characteristics and the pattern of between-domain relations of academic emotions differs with respect to the method of assessment (trait vs. state). It is important to note that There are some limitations as well as a number of practical implications related to our studies. One limitation is that in Study 1 only one interview question was used for eliciting students' responses about domain characteristics. Because we targeted seven different academic domains, it was not feasible to ask additional questions due to potential weariness resulting from the repetitive nature of such interview. Future studies might focus on fewer domains and assess salient domain characteristics from students' perspective in more detail. Another potential shortcoming of the present series of studies is that the employed design did not allow for establishing a causal ordering of effects. Although theoretical approaches  might differ from what he or she This is in line with a recent finding showing that compared to boys, girls overestimate their math anxiety due to their lower math-related academic self-concept despite having similar grades as boys (Goetz et al., The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Infections with bovine respiratory syncytial virus (BRSV) and bovine coronavirus (BoCV) are endemic to the cattle populations in most countries, causing respiratory and/or enteric disease. It has been demonstrated that herds can remain free from these infections for several years also in high prevalence areas. Organically managed (OM) dairy herds have been shown to have lower seroprevalence of both viruses compared to conventionally managed (CM) herds. The objective of this study was to challenge the hypothesis of a lower occurrence of BRSV and BoCV in OM compared to CM dairy herds.In November 2011, May 2012 and May 2013 milk samples from four homebred primiparous cows were collected in 75 to 65 OM and 69 to 62 CM herds. The antibody status regarding BRSV and BoCV was analysed with commercial indirect ELISAs. Herds were classified as positive if at least one individual sample was positive.The prevalence of positive herds ranged from 73.4% to 82.3% for BRSV and from 76.8% to 85.3% for BoCV among OM and CM herds, over the three sampling occasions. There was no statistically significant difference between OM and CM herds at any sampling occasion. The incidence risk of newly infected herds did not differ statistically between OM and CM herds at any sampling occasion, neither for BRSV nor for BoCV. The incidence of herds turning sero-negative between samplings corresponded to the incidence of newly infected. Bulk tank milk (BTM) samples were also sampled in the herds and analysed. Several herds were negative on individual samples but positive in BTM. Herd-level data on production, health and reproduction were retrieved from VÄXA Sweden and the study herds were representative of the source population.There was no difference in prevalence of or incidence risk for BRSV or BoCV between Swedish OM and CM herds. Because the incidence of herds becoming seropositive was balanced by herds becoming seronegative it should be possible to lower the prevalence of these two infections among Swedish dairy cattle herds if biosecurity is improved.The online version of this article (doi:10.1186/s13028-014-0091-x) contains supplementary material, which is available to authorized users. Infections with bovine respiratory syncytial virus (BRSV) -4 and boBRSV commonly cause respiratory disease, particularly in calves. Disease can be caused by BRSV only or in combination with other viruses (e.g. BoCV) or secondary bacterial infection -11. BoCVet al. [After infection with BRSV or BoCV animals will remain seropositive for several years. This was demonstrated by Bidokti et al.  who founet al. ,21, i.e.et al. . When thAlthough these viruses may spread during the warmer seasons, seroconversion with or without an outbreak of clinical disease is more frequent during the housing season (autumn and winter) ,23,24. TA recent study found that organically managed (OM) dairy herds had significantly lower seroprevalence of both BoCV and BRSV compared to conventionally managed (CM) herds. However, the study could not explain the reason for the differences in the two production systems . AlthougThis was a prospective longitudinal observational study including OM and CM dairy herds. The unit of interest was herd.www.krav.se), the Swedish member of the International Federation of Organic Agriculture Movements.The sampling frame was all dairy herds with a yearly average herd size of at least 50 cows and enrolled in the Swedish Official Milk Recording Scheme. The inclusion criterion of a yearly average herd-size of at least 50 cows was chosen to exclude small herds which do not represent the “future” herd. Geographically, all counties except for most southern Skåne were included. Skåne was excluded because it was known that there are very few BRSV and BoCV negative herds in this region. OM herds were defined as herds with a dairy production certified according to the standards by the association KRAV  were sent a written invitation to the study in May 2011. In total, 75 (31%) and 69 (17%) of farmers with OM and CM herds, respectively, agreed to participate in the project. Participants gave a written permission to access the herd’s data from the milk recording scheme.Study herds were sent instructions, material and protocol for sampling in November 2011, May 2012, and May 2013. These occasions were chosen to include as many stall periods as possible during the project. At each sampling occasion, milk from four homebred primiparous cows and BTM were sampled into test tubes with 1.5 mg of the preservative agent Bronopol. Samples were returned to the National Veterinary Institute by prepaid mail where they were stored at −20°C until analysed.The antibody status regarding BRSV and BoCV was analysed with the commercial indirect ELISAs . The optical density (OD) of samples was corrected by subtraction of negative control OD, and the percent positivity (PP) value was calculated as the corrected OD divided by the corrected OD for positive controls and multiplied by 100. The samples from individuals were classified as negative if PP < 10, following the manufacturer’s guidelines, and bulk tank samples if PP < 5. The sensitivity and specificity of the ELISA test kit was 94% and 100%, respectively, for BRSV and 84.6% and 100%, respectively, for BoCV, according to the manufacturer.After each completed sampling occasion, the farmers were sent information on their herd’s serological status and information about basic biosecurity measures. A lottery ticket  was enclosed to the letter.Antibody status as measured in individual milk samples was used as an indicator of the herd’s recent infection status regarding the two viruses. Herds were defined as antibody positive if at least one of four samples from individual cows was positive. A stricter definition of positive herd where all four individual samples had to be positive was also applied. To assess any difference in antibody status between OM and CM herds, the prevalences of positive herds at each sampling occasion among OM and CM herds, respectively, were calculated with exact binomial confidence intervals using the package “binom” for R . Data maFurther, the incidence risk with exact binomial confidence intervals was calculated for the samplings in 2012 and 2013, for OM and CM herds, respectively. The period at risk was from the last sampling occasion, i.e. 6 months and 12 months, respectively.To explore if there were differences in antibody level in the bulk tank milk between the CM and OM herds, the results from the BTM samples  were categorised into six groups; PP < 5, 5 ≤ PP < 10, 10 ≤ PP < 30, 30 ≤ PP < 60, 60 ≤ PP < 100, and 100 ≤ PP. The frequencies of OM and CM herds in each group were tabulated for each year and virus.Data on herd production, health and reproduction were retrieved from the Swedish Official Milk Recording Scheme database managed by VÄXA Sweden for all selected herds, i.e. including also the invited but non-participating herds. The information included averages of routinely collected parameters for the 12 months before the start of the study.Herd parameters were described and tested for difference between the OM and CM herds that participated in 2011 i.e. entered the study, using a two-sided Wilcoxon rank-sum test or Fischer exact test. To study how the study group characteristics were affected from drop-out herds leaving the study, herd parameters were described for the subsample of OM and CM study herds that completed the last sampling in 2013. To examine the representativeness of the study herds, herd parameters were also described for all invited OM and CM that did not participate in the study.The number of study herds per year was 144, 132, and 127 in 2011, 2012 and 2013, respectively  and negative after six months was 33% and 42%, respectively . A high et al. [Many of the herds with positive BTM samples, but with a low PP value, i.e. <30 had only negative individuals. This indicates that there had been no virus circulating in the herd the last 2 to 3 years (Table et al.  where alet al. . Also, tet al.  using thA limitation of the study is the less than perfect sensitivity of the two ELISA tests used. Because the aim was to compare OM and CM herds, the true prevalence or incidence risk was not estimated. Any misclassification bias due to test characteristics should be the same in the two groups. Further, the different lengths of period at risk for the incidence estimates at the second and third sampling occasions was not optimal, because it made comparisons between sampling occasions impossible. This, however, does not influence the comparison of OM and CM herds at the same sampling occasion. However, this comparison could have been improved with a larger number of study herds. For example, the number of herds going from positive to negative or the opposite was now low and the confidence intervals of estimates wide. It would also have been beneficial with a longer total study period, thus including more than two housing periods, and more frequent sampling to explore how herds’ status change over time with better precision.We consider the OM and CM study herds as representative of the OM and CM dairy herds in Sweden, because their production and health parameters did not differ substantially from the invited but non-participating herds (Additional file There was no difference in prevalence of or incidence risk for BRSV or BoCV between organically and conventionally managed dairy herds in Sweden. The incidence risk of herds becoming seropositive was balanced by herds becoming seronegative, but with improved biosecurity it should be possible to lower the prevalence of these two infections among Swedish dairy cattle herds.


The insecticidal IE648 toxin is a truncated Cry1Ie protein with increased toxicity against Asian corn borer (ACB). Cry toxins are pore-forming toxins that disrupt insect midgut cells to kill the larvae. However, the peritrophic membrane (PM) is an important barrier that Cry toxins must cross before binding to midgut cells. Previously, it was shown that Cry toxins are able to bind and accumulate in the PM of several lepidopteran insects. Binding of IE648 toxin to PM of ACB was previously reported and the goal of the current work was the identification of the binding region between Cry1Ie and the PM of ACB. Homologous competition binding assays showed that this interaction was specific. Heterologous competition binding assays performed with different fragments corresponding to domain I, domain II and domain III allowed us to identify that domain III participates in the interaction of IE648 with the PM. Specifically, peptide D3-L8 (corresponding to Cry1Ie toxin residues 607 to 616), located in an exposed loop region of domain III is probably involved in this interaction. Ligand blot assays show that IE648 interact with chitin and PM proteins with sizes of 30, 32 and 80 kDa. The fact that domain III interacts with proteins of similar molecular masses supports that this region of the toxin might be involved in PM interaction. These data provide for the first time the identification of domain III as a putative binding region between PM and 3D-Cry toxin. Bacillus thuringiensis (Bt) is the most successful insect pathogen used for insect control, constituting 2% of the total insecticidal market [Crop production has been compromised by insect pests since the beginning of agriculture. Insect control is now mainly achieved by chemical insecticides. However, this practice has resulted in serious negative effects on the environment because of their toxicity to non-target animals and humans . The bacl market . Insect l market –7.cry1I genes [cryV before Bt nomenclature standardization [Escherichia coli cells. Cry1I proteins, which have a molecular mass of 81 kDa, are toxic to various lepidopteran larvae such as Ostrinia nubilalis and Epiphyas postvittana [Leptinotarsa decemlineata [Tenebrio molitor [Culex pervigilans [50 to Plutella xylostella 1112.43 ng/mL) compared to the full-length Cry1Ie protein (LC50 to Plutella xylostella 1685.88 ng/mL) [The Bt 1I genes  (formerldization ) are siltvittana –12. Cry1 molitor ; and onevigilans . The tru8 ng/mL) . IE648 d8 ng/mL) .The peritrophic membrane (PM) of insects acts as the major barrier through which Cry toxins must cross before binding to receptors located in the brush border membrane. PM is an insoluble acellular matrix consisting of chitin fibrils and tightly associated proteins called peritrophins. This matrix separates the ingested food in the gut from the gut epithelium . Chitin,Bombyx mori PM is higher for Cry1Aa than for Cry1Ac, which correlates with the higher sensitivity of the B. mori larvae to Cry1Aa than to Cry1Ac [Cydia pomonella granulovirus GP37 and chitinase have been investigated. These agents resulted in a significant enhancement of the lethality of Bt toxins in various types of larvae [Previously, it was shown that Cry toxins are able to bind to and accumulate in the PM of various lepidopteran insects ,17,19–23o Cry1Ac . To imprf larvae –29.IE648, is a 3D-Cry toxin, that shows important insecticidal effect against ACB . It was cry1Ie gene, containing the first 648 amino acid residues of Cry1Ie, cloned in vector pET-21b (Novagen) and named pET1Ie-648 [E. coli BL21 (DE3), from Novagen. The full length of cry1Ie gene [In this work we used a truncated version of T1Ie-648 . This reNi-Agarose was purchased from QIAGEN. All other reagents were local products of analytical grade. All peptides were synthesized by SBS Co. Ltd in Beijing, China. Chitin  from shrimp shells is from Sigma. Inclusion Body Solubilization and Refolding Kit from Tiandz, Inc Co. Ltd in Beijing, China. Biotin Tag Micro Biotinylation Kit from Sigma-Aldrich Co. LLC, United States.cry1Ie are shown in BamHI and SalI and inserted into vector pET21b. Transformed E. coli JM110 were selected with 100 μg/ml ampicillin. Gene fragments encoding different domains of Cry1Ie were confirmed by DNA sequencing. E. coli BL21 (DE3) cells were transformed with each recombinant plasmid for expression.Primer sequences for amplification of three domains of E.coli BL21 (DE3) containing the corresponding recombinant plasmid, induced by 0.4 mM IPTG at 20°C for 20 h. The three domains were all expressed mostly as inclusions. Purification of domain I was described in a previous report [2CO3, pH 10.2 as same as domain I. Domain II was dissolved by using the solubilization solutions of Inclusion Body Solubilization and Refolding Kit. After dissolved they were both purified by Ni-NTA (QIAGEN) as they have His-tags in their N-terminal, just like domain I, but different elution requirements. Domain II was eluted with 50 mM Na2CO3, pH 10.2. Domain III was eluted by 50 mM imidazole . Each one of the there domains present in Cry1Ie toxin has several lysine residues , thus the purified domains were efficiently labeled with biotin using the BAC-Sulfo-NHS of Biotin Tag Micro Biotinylation Kit following the procedure of the kit and biotin labeling was verified through dot blotting.IE648 protein was purified as previously described . The difs report . The incet al. [BBMV were prepared from midgut tissue isolated from fourth-instar ACB as described by Jurat-Fuentes et al. . AminopeThe entire larval PM was removed from midgut tissue and washed twice in cold phosphate buffered saline (PBS) before it was homogenized in cold PBS with protease inhibitors on ice using a Dounce homogenizer for 30 strokes . The proTwenty micrograms of BBMV or PM proteins of ACB were incubated with 10 nM biotinylated IE648 in the presence or absence of a 50- to 1000-fold excess of unlabeled toxin in binding buffer  for 1 h. The unbound toxin was removed by centrifugation for 10 min at 14,000 ×g. The BBMV or PM pellets were suspended in 100 μl of binding buffer and washed twice with the same buffer. Finally, the BBMV or PM were suspended in 20 μl of PBS, pH 7.6, and an equal volume of 2X-Laemmli sample loading buffer  was added. Samples were boiled 5 min, loaded onto SDS—PAGE and electrotransferred to PVDF membranes . The bioForty micrograms of insoluble chitin was incubated with 10 nM biotinylated protein  in binding buffer  for 1 h. The unbound toxin was removed by centrifugation for 10 min at 14,000 ×g. The pellet was suspended in 100 μl of binding buffer and washed twice with the same buffer. Finally, the pellet was suspended in 20 μl of PBS, pH 7.6, and an equal volume of 2X -Laemmli sample loading buffer was added. Samples were boiled 5 min, loaded onto SDS—PAGE and electrotransferred to PVDF membranes . The bioPM of 20 ACB larvae were separated into four classes of components. S1 is the suspension obtained after PM dissolving in 1% Triton X-100 for 1 h at room temperature. Then grind the PM suspending in 1% Triton X-100. S2 is the homogenate obtained after grinding. S3 is the supernatant obtained after the centrifugation of the homogenate and S4 is the pellet obtained after the centrifugation. After SDS-PAGE of the four PM constituents (S1–S4), the PM proteins in the gel were electrotransferred onto PVDF membranes. The membranes were blocked by incubation with 5% BSA in PBS, pH 7.6 for 1 h, followed by washing five times for 10 min each with washing buffer (PBS containing 0.05% Tween 20). Then the membranes were incubated with 10 nM biotinylated toxin or domains in PBS for 1 h. Unbound toxin or domains were removed by washing with washing buffer five times for 10 min each. The biotinylated protein that remained bound to the membranes was revealed by incubation with streptavidin-peroxidase conjugate  for 1 h and visualized using the ECL Western Blotting Substrate (Pierce) according to the manufacturer’s directions.To determine which region of Cry1Ie is involved in binding to PM, the three structural domains were defined by multiple sequence alignments with other Cry toxins and a model of the three dimensional structure of Cry1Ie toxin was constructed. According to the multiple sequence alignment of the Cry toxins  and the structural predictions generated by Swiss Modeling, different domains of Cry1Ie toxin were designated as follows: domain I includes amino acids M1-T280, domain II includes amino acids V282-D497, and domain III includes amino acids T501-M719.E. coli hosts. The different domains were produced as inclusion bodies, with expected molecular masses of 34.6 kDa for domain I, 27.3 kDa for domain II, and 27.9 kDa for domain III   , lane 3,Homologous and heterologous competition binding assays were conducted to determine whether IE648 can bind to PM. The results indicated that IE648 specifically binds to the PM of ACB as shown by the homologous competition binding assay . The hetTo narrow further the IE648 domain III binding site, several synthetic peptides of domain III were synthesized based on the sequence BLAST and structural model analysis, including conserved peptides and peptides corresponding to the exposed loops. According to a protein BLAST analysis, Cry1Ie toxin has the highest identity with Cry1Aa (34.46% identity) and Cry8E (37.18% identity). Manduca sexta [Three conserved peptides of domain III , indicatca sexta . Two speSeveral conserved peptides and peptides located in the loop regions of domain II were also synthesized and analyzed. Quite weak competition of two peptides (D2-L1 and D2-L7) could be observed in the competitive binding of IE648 to PM of ACB, which corroborated the weak binding competition of domain II with IE648  panel 2CTo determine whether binding of IE648 to PM involves interactions with proteins or chitin from the PM, we first analyzed the binding with PM proteins by ligand-blot assays. To analyze the binding of IE648 with chitin, insoluble chitin was incubated with biotinylated IE648 protein and the bound toxin was separated by centrifugation as described in experimental procedures. The chitin we used in this study is a commercial chitin derived from shrimp. cry1Ie gene in E. coli and in transgenic tobacco confers resistance to corn borer [Homologous competition binding assays of IE648 to PM from ACB indicated that IE648 binding was specific. Heterologous competition binding assays with the different domains showed that domain II and III competed the binding of IE648 to PM, although domain III fragment was more efficient than domain II in competing binding of IE648 to PM. It is reported that one site of Cry1Ac domain III can recognize the GalNAc on APN receptor . We infern borer . The accSpecific peptides were designed based mainly on their sequence conservation among the Cry toxins, their role in BBMV binding as previously reported and on their structural location. The synthetized peptides covered most of domain III sequence excluding a small 8 residue region (Y599-G606) and 4 amino acid region at the end of domain III (V645-E648). Since no clear binding competition was observed, it is possible that the interaction with PM is conformation dependent and requires 3-dimensional structure to properly position contact points to have significant affinity. It has been reported that domain III of Cry toxins shares a folding structural similarity with different carbohydrate binding domains ,37. Thuspodospora anserina GH26-CBM35 beta-- mannanase , the other is carbohydrate binding module of the CBM35 family of Glucuronoxylanase Xyn30D . They both have molecular function of carbohydrate binding. This indicates that domain III of Cry1Ie have carbohydrate binding potential. Chitin is a long chain polymer of GlcNAc, it is a characteristic component cell walls in fungi and exoskeletons of arthropods such as crustaceans and insects [PM consists of chitin fibrils and tightly associated proteins. In our result, three domains were found to bind with both chitin and the PM protein, just like the whole IE648 toxin. This binding ability to polysaccharide of Cry1I toxins has never been reported before. Chitin is a polysaccharide composed of β-1,4 linked N-acetylglucosamine (GlcNAc). As discussed above, it was reported that the structure of domain III of Cry1Aa resembles carbohydrate-binding protein domains . Similar insects . Valaiti insects . The staThis is the first report that describes that Cry toxins bind PM through domain III. Further work defining the specific amino acids involved in binding to PM by site directed mutagenesis of domain III that affect binding to PM without affecting binding to receptors in BBMV is likely to provide information that could reveal the role of PM binding in Cry toxicity.S1 File(Table A). Heterologous competition binding assays of IE648 to PM and BBMV from Asian corn borer with different peptides from domain II .Peptides of Cry1Ie domain II (RAR)Click here for additional data file.


Ornithodorus moubata complement inhibitor (OmCI), in contrast to eculizumab, maintained anti-haemolytic function for mutations in any of the six epitope residues, thus representing a possible alternative treatment for patients non-responsive to eculizumab. The method for stratification of patients described here allows for precision medicine and should be applicable to several other diseases and therapeutics.The complement component 5 (C5)-binding antibody eculizumab is used to treat patients with paroxysmal nocturnal hemoglobinuria (PNH) and atypical haemolytic uremic syndrome (aHUS). As recently reported there is a need for a precise classification of eculizumab responsive patients to allow for a safe and cost-effective treatment. To allow for such stratification, knowledge of the precise binding site of the drug on its target is crucial. Using a structural epitope mapping strategy based on bacterial surface display, flow cytometric sorting and validation via haemolytic activity testing, we identified six residues essential for binding of eculizumab to C5. This epitope co-localizes with the contact area recently identified by crystallography and includes positions in C5 mutated in non-responders. The identified epitope also includes residue W917, which is unique for human C5 and explains the observed lack of cross-reactivity for eculizumab with other primates. We could demonstrate that  The term precision medicine describes the idea of providing effective treatment based on a patient’s molecular make up. Recent advances in molecular diagnostic tools and handling of large data sets allow for the stratification of patients based on e.g. genetic or protein information and make it possible to provide tailored treatment for these sub-groupsThe complement system is an important part of the human innate immunity. It fulfils an important role in fighting bacterial infections and homeostasis and provides a link between innate and adaptive immune response34457The monoclonal antibody eculizumab (Soliris®) is the first FDA-approved therapeutic antibody for treatment of PNH245772412141618192122Despite the proven relevance of the drug, reports on non- or poorly responding patients have been published24252627et al.Different efforts have been undertaken to identify the binding site of eculizumab on C51129Staphylococcus carnosus (S. carnosus)3537S. carnosus. The combination of random mutagenesis and surface display of protein domains allows a more thorough analysis of the mutational space under native-like conditions in contrast to other high-throughput mapping techniques like peptide arrays and alanine scanning.Here, we used an epitope mapping strategy based on deep mutational scanning of surface-displayed protein domains to explore in detail the structural epitope properties of eculizumab. While high-resolution X-ray crystallography of the antibody complex still represents the gold standard for epitope determinationThe presented workflow  includesThe complement factor C5 has been structurally characterized and found to consist of twelve domains394 clones and sequencing of 96 randomly picked clones revealed a mutation frequency of 1.4 nucleotide mutations per gene (data not shown). The albumin-binding protein (ABP), expressed in fusion with the respective mutated domain before the membrane anchoring domain, was used with labelled human serum albumin (HSA) to detect surface expression of the domain. Mutations within MG7 leading to overall misfolding of the domain or introduction of stop codons were expected not to be secreted nor properly anchored to the cell surfaceHaving identified the MG7 domain as the binding domain for eculizumab, a random mutagenesis library of this domain was constructed by error-prone PCR  were expressed and purified from transiently transfected CHO cells. A C-terminal protein C peptide tagThe nine mutant C5 proteins together with the wild type C5 were analysed for binding to eculizumab by sandwich ELISA. The analysis confirmed that many of the mutants, except I829K and V896E, showed reduced binding . AlthougOrnithodorus moubata complement inhibitor (OmCI), a tick protein43The haemolytic activity, i.e. the ability to elicit C5b-9 formation, was analysed for the recombinant C5 variants that showed reduced binding to eculizumab in ELISA to exclude that the drop in binding is due to a major structural change brought about by the mutation. The analysis shows that all mutants are able to induce C5b-9 formation in a concentration-dependent manner , althougi.e. Q854, F855, R885, K887, W917 and F918. These residues are widely spread over the MG7 protein sequence  were searched for missense mutations in MG7. Altogether 32 naturally occurring variations in the MG7 domain were found, listed in It has been reported that eculizumab is specific for human C5 and that the lack of reactivity of orthologous C5 proteins has prohibited use of such animal modelsS. carnosus and domain MG7 was identified as the binding domain of the therapeutic antibody eculizumab. A deep mutational scanning of MG7 was performed to determine the amino acids involved in eculizumab binding. After excluding multiple mutations and mutations to or from cysteine, glycine and proline that are likely to disrupt the protein structureThis work presents six residues on the complement protein C5 that are essential for the binding and function of the therapeutic antibody eculizumab and suggest that other means of treatment should be considered for individuals carrying mutations in these positions. All 12 domains of C5 were successfully expressed on the cell surface of et al. report three contact regions on C5 within the β-sheet of MG7 comprising residues 851–858, 882–888 and 915–920. Although the resolution of the crystallographic data did not allow the clear identification of single epitope residues, the authors inferred from the existence of binding pockets on the antibody that residues W917, F918 and R885 are involved in binding. All three residues could be confirmed to be essential for antibody binding by the surface display based epitope mapping approach presented here. In addition, three other residues, Q854, F885 and K887, which locate in the first and second contact region, described by Schatz-Jakobsen et al.This hypothesis was confirmed by the C5-eculizumab Fab co-crystal structureet al.et al. also hypothesised that a cysteine mutation at that position could affect the disulphide bridge between residues 856 and 883. We observed a decreased haemolytic activity for the R885C mutant which could be explained by a structural change in the MG7 domain that perturbs interaction of this domain with the convertaseOur binding assays with full-length C5 variants from mammalian sources have shown that the findings about the eculizumab epitope on domain level on the staphylococcal surface are transferable and relevant for full-length human C5. Analysis of surface exposure reveals that all residues but F855 exceed 25% surface exposure. This might account for the lower degree of haemolytic activity, i.e. a higher degree of inhibition by eculizumab, observed for this mutant in the haemolysis inhibition assay . As SchaThe clinical relevance of R885-mutations is highlighted by a study on Japanese PNH patientsMoreover, it could be shown that the C5 complement inhibitor OmCI, which binds at a site distinct from eculizumab30454647et al.S. carnosus is achieved as described beforeE. coli and purified prior to transformation of S. carnosus TM 300 cells . S. carnosus cells were transformed by electroporation using a Bio-Rad MicroPulser electroporator at 2.3 kV for 1.1 ms. Transformed cells were grown at 37 °C overnight for protein surface expression. Having identified the C5 MG7 domain as binding domain of eculizumab (produced from CHO cells at Swedish Orphan Biovitrum AB (Sobi), Stockholm, Sweden, M.M.B, Chao Su, Lotta Berghard, Göran Selén, Kerstin Larsson, Joakim Nilsson, Catharina Sterky, Carina Ekholm, Per-Olof Edlund, Charlotte Söderberg Nyhem, P.S., manuscript in preparation), the domain was amplified using a Genemorph random mutagenesis kit  to yield an average mutation frequency of 1.4 mutations per sequence. The vector was purified by phenol chloroform extraction and cloned into S. carnosus as described above.The mRNA sequence for C5 was obtained from Source BioScience . The C5 domains according to Fredslund S. carnosus overnight culture 2 μL were taken for analysis. The cells were washed twice with phosphate buffered saline containing 0.1% pluronic  (PBS-P) before incubation with eculizumab (8.8 nM) for 45 min at room temperature. The cells were then washed with PBS-P and incubated with Alexa 488-labeled goat-anti-human secondary antibody (2 μg/mL) and Alexa 647-labeled HSA (1:1000 dilution) for expression control on ice in the dark for 30 min. After a final washing step the cells expressing the protein domains were analysed in a Gallios flow cytometer . The same protocol was also applied when analysing the identified library clones individually.Of an The library clones were labelled in the same way as described above. The cells were analysed and sorted in a MoFlo Astrios cell sorter . The library was sorted for binding escape mutants that show a pertained high surface expression signal but a decreased antibody-binding signal. Two rounds of sorting for binding escape mutants were performed with the sorting gates indicated in The gene for human C5 was cloned into vector pQMCF1 coding for full-length C5 protein C-terminally fused to a tobacco etch virus-protease site and a Human protein C epitope tag (HPC4). C5 mutants were derived from this plasmid by using the Q5® Site-Directed Mutagenesis Kit . Successful mutagenesis was confirmed by Sanger sequencing. Recombinant wildtype and mutant C5 was expressed in Chinese hamster ovary (CHO) EBNALT 85 cells  following the manufacturer’s guidelines for extended transient expression. After 15 days of cultivation C5 proteins were purified from the cell culture supernatant by affinity chromatography on an anti-protein C affinity matrix . Due to low protein concentration, some samples were concentrated using a centrifugal filter . Protein concentration was determined with ImageJ see  from a Cet al.Binding of recombinant wildtype and mutant C5 was assessed by ELISA. A 96-well half area plate was coated overnight with 33.3 nM OmCI  were used and the amount of hemolysis was monitored as absorbance at 415 nm. Diluted C5 deficient human serum (1:50) was spiked with C5 (WT or mutant) at different concentrations ranging from 51.2 nM to 6.25 pM. Subsequently, the capacity to inhibit haemolytic activity by eculizumab and OmCI at 100–0.001 nM was monitored using C5 concentrations optimized to normalize haemolytic activity between C5 variants; 0.023 nM (WT), 0.013 nM (Q854L), 0.011 nM (F855I), 8.9 nM (R885C), 0.089 nM (R885H), 0.046 nM (K887N), 0.72 nM (W917L), 1.6 nM (W917S) and 0.089 nM (F918S).The ability of WT and mutated C5 to form C5b-9 was monitored by haemolytic activity using antibody  coated sheep red blood cells. 5 × 10Pan troglodytes), crab-eating macaque (Macaca fascicularis), rhesus macaque (Macaca mulatta), cat (Felis catus), wild boar (Sus scrofa), cow (Bos taurus), rat (Rattus norvegicus) and mouse (Mus musculus). The amino acids at the six identified positions were analysed for species conservation.The six identified amino acid mutations were visualized on an existing 3D structure of C5 (PDB5I5K)The mean of duplicates or triplicates is depicted in all column charts. Error bars indicate standard deviation. Statistical significance was calculated using GraphPad Prism Software. One-way Analysis of variance (ANOVA) with Dunnett’s multiple comparison test and two-way ANOVA with Tukey multiple comparison test was applied for ELISA results and haemolytic activity testing, respectively.How to cite this article: Volk, A.-L. et al. Stratification of responders towards Eculizumab using a structural epitope mapping strategy. Sci. Rep.6, 31365; doi: 10.1038/srep31365 (2016).