Evolutionary innovation in eukaryotes and especially animals is at least partially driven by genome rearrangements and the resulting emergence of proteins with new domain combinations, and thus potentially novel functionality. Given the random nature of such rearrangements, one could expect that proteins with particularly useful multidomain combinations may have been rediscovered multiple times by parallel evolution. However, existing reports suggest a minimal role of this phenomenon in the overall evolution of eukaryotic proteomes. We assembled a collection of 172 complete eukaryotic genomes that is not only the largest, but also the most phylogenetically complete set of genomes analyzed so far. By employing a maximum parsimony approach to compare repertoires of Pfam domains and their combinations, we show that independent evolution of domain combinations is significantly more prevalent than previously thought. Our results indicate that about 25% of all currently observed domain combinations have evolved multiple times. Interestingly, this percentage is even higher for sets of domain combinations in individual species, with, for instance, 70% of the domain combinations found in the human genome having evolved independently at least once in other species. We also show that previous, much lower estimates of this rate are most likely due to the small number and biased phylogenetic distribution of the genomes analyzed. The process of independent emergence of identical domain combination is widespread, not limited to domains with specific functional categories. Besides data from large-scale analyses, we also present individual examples of independent domain combination evolution. The surprisingly large contribution of parallel evolution to the development of the domain combination repertoire in extant genomes has profound consequences for our understanding of the evolution of pathways and cellular processes in eukaryotes and for comparative functional genomics. Most proteins in eukaryotes are composed of two or more domains, evolutionary independent units with (often) their own individual functions. The specific repertoire of multidomain proteins in a given species defines the topology of pathways and networks that carry out its metabolic and regulatory processes. When proteins with new domain combinations emerge by gene fusion and fission, it directly affects topology of cellular networks in this organism. To better understand the evolution of such networks we analyzed a large set of eukaryotic genomes for the evolutionary history of known domain combinations. Our analysis shows that 70% of all domain combinations present in the human genome independently appeared in at least one other eukaryotic genome. Overall, over 25% of all known multidomain architectures emerged independently several times in the history of life. The difference between a global and species specific picture can be explained by the existence of a core set of domain combinations that keeps reemerging in different species, which are accompanied by a smaller number of unique domain combinations that do not appear anywhere else. Most eukaryotic proteins are composed of multiple domains, units with their own evolutionary history and, often, specific and conserved functions. The ordered arrangement of all domains in a given protein constitutes its architecture. Protein architecture can also be described in a simplified way as a list of binary domain combinations. While not completely equivalent, both views provide similar insights, and in this manuscript we will predominantly use the latter. Many domains can combine with different partner domains and, as a result, form a wide variety of domain combinations, often even within the same species The domain repertoires of most eukaryotes are remarkably similar, both in size as well as in their content However, one can expect that the process of domain shuffling could lead not only to the emergence of completely new domain combinations, but also to the independent emergence of domain combinations already present in other, even distantly related, organisms. In fact, it has been shown that certain domain combinations observed in proteins involved in innate immunity have evolved independently several times Capsaspora owczarzaki as the sole representative of Filasterea , the single-celled ciliate Tetrahymena thermophila (44%), and the single-celled parasite Trichomonas vaginalis (47%). The likely explanation for these low coverages is that these genomes contain a large percentage of domains not found in the traditional model organisms, which are therefore not yet included in the Pfam database. The genome of the pufferfish Takifugu rubripes, on the other hand, has the highest coverage level at 94%. For the human genome, this percentage is 85%.All proteins from all genomes were analyzed for the presence of protein domains, as defined by the Pfam database (version 25.0) Overall, 34,778 distinct domain combinations were found in the 172 genomes analyzed here. A total of 22,241 of these appear in just one genome, and only 33  is described as a set of the three binary combinations A∼B, B∼C, and A∼C. We retained information about the domain order, i.e., domain combination A∼B is not the same as B∼A. Combinations between the same domains were not included in the analysis . The rationale for this is that combinations between the same domains can be a result of local duplication, ancestral descent, or domain fusion and the only approach to distinguish between these would be by explicit phylogenetic analysis of each domain.First, we simply counted how many distinct domains and domain combinations each of the 172 genomes contains. The average number of domains per protein is 1.7 for all the genomes analyzed here; however, for animal genomes this number is higher (2.0). The distribution of domains in multidomain proteins is not uniform, with 1,448 domains appearing exclusively in single-domain proteins and 535 appearing only in multidomain proteins  and Chlorophyta , have proportionally fewer domain combinations than the other groups. On the other hand, Alveolata  appear to partially compensate for their limited number of domains by having a comparatively large number of domain combinations .The number of distinct domains per genomes shows little variance between different organisms (with the exception of some parasitic species) and, when including inferred sets for the ancestral species, generally displays a decreasing trend in going from the last common eukaryotic ancestor to large multicellular organisms Branchiostoma floridae (amphioxus), for which no close relative has been sequenced so far, is one of the exceptions, with about 2,140 species-specific domain combinations. The next-most-prolific organisms in terms of the number of unique domain combinations are the hemichordate Saccoglossus kowaleskii (“acorn worm”) with about 850 species-specific domain combinations, the brown tide heterokont (stramenopile) Aureococcus anophagefferens (∼760), the purple sea urchin Strongylocentrotus purpuratus (∼720) . In all likelihood, in most cases the large number of unique domain combinations of these organisms is partially due to the fact that they are the sole sequenced representatives of their respective (sub-)phyla, and their domain combination counts have to be compared with those of the entire phyla, such as Arthropoda, which has about 1,500 clade-specific domain combinations (based on 12 genomes). On the kingdom level, animals clearly have the most clade-specific domain combinations , whereas Embryophyta (land plants) and fungi both have less than half that number. Clade-specific domain and domain combination numbers for select taxonomic groups are shown in As mentioned above, in our analysis of 172 genomes, 22,241  domain combinations appear only once and thus are specific to a single species. These species-specific domain combinations are relatively evenly distributed, with 95 out of the 172 analyzed genomes having between 10 and 100 domain combinations that are specific to the individual species , with a median value of 57 . In contrast, only 14% are specific to fungi, despite fungi having the largest numbers of genomes analyzed in this work. Thirteen percent of all domain combinations are not supergroup-specific, i.e., they appear in at least two different supergroups. Only 2% of all domain combinations are found in representatives of all five eukaryotic supergroups analyzed in this work . We also investigated the numbers and types of domain combinations that are not only exclusive to a given clade, but also appear in Micromonas). All the clades in-between lack this combination, even though they possess each of the individual domains. Therefore, the KH-1∼DEAD was likely to have been “rediscovered” two times .Next, we investigated the evolutionary history of domain combinations—do they tend to appear once and are then inherited by the descendants  and the obligate intracellular parasite Encephalitozoon cuniculi the lowest (24.4%)  and is slightly longer than that of proteins with non-reappearing domain combinations that have an average of 712 residues (median: 534). On the other hand, the average number of domains in these two groups is almost identical (∼3.3). We also compared the average lengths of domains themselves in those two groups. The results support the observation that repeated domain combinations tend to appear in longer multidomain proteins, but the preference is not very strong.−3 to 1e−15), as well as domain-specific “trusted” and “noise” cutoff scores from the Pfam database  We also investigated how the specific choices of parameters affect these numbers. In particular, we tested a range of cutoff E-values  for each pair of independently evolved domain combinations and then counted for each internal node of the eukaryotic tree of life for how many pairs of independently evolved domain combinations it represents the LCA. These counts were then normalized by the sum of species emerging from each node. The results for the nodes with the highest rates are summarized in In the following, we present some examples of parallel evolution of domain combinations between animals and fungi, Amoebozoa, and green plants see  to 10.An example of independent domain combination evolution between animals  and Dikarya (that subkingdom of fungi that includes the two major phyla Ascomycota and Basidiomycota) is shown in Dictyostelium ∼DEAD/DEAH box helicase combination that appeared independently in Bilateria and in Micromonas  . The K hAll the values presented here depend critically on the number and phylogenetic distribution of genomes analyzed, the size of the domain database, and the significance thresholds (and sensitivity) for domain assignments. We evaluated the effects of these on our results, especially in the light of many earlier papers reporting results of somewhat similar analyses being contradictory to our results. To understand these apparent discrepancies, we have repeated our analyses using a reduced number of genomes, different domain recognition thresholds, and smaller domain databases mimicking the approaches used in earlier works. The results from these analyses confirm that the differences between the earlier and the current results stem mostly from the increase in the number of analyzed genomes and in the size of the domain databases. For instance, using only five genomes resulted in a reemergence percentage similar to the estimates presented in . Clearly−2 used in −2 instead of the domain-specific “gathering” thresholds results in a multidomain protein percentage of 52 (and a protein match range of 52% to 97%), which is still lower than reported in Similarly, we can show that other differences between our results and that of the previous analyses are mostly due to the changes in the number of genomes and the size of the domain database. For instance, analysis of five eukaryotic genomes and domain definitions from the SCOP 1.53 database Branchiostoma floridae). Furthermore, we performed our analysis on various subsets of all available eukaryotic genomes that are believed to be of high(er) quality (results not shown). In both cases, the effect on the resulting parallel evolution rate of 27% was negligible.Unfortunately, we cannot completely exclude the effects of erroneous gene models. To partially address this problem, we performed our analysis under both inclusion as well as exclusion of the one genome with the most unusual domain combinations , our results do not take into account parallel domain combination evolution within a genome, i.e., between paralogs in large protein families .Finally, we would like to point out while the tree of life shown in Our analysis shows that the number of distinct domain combinations per genome varies greatly between different groups of species and increases systematically with their complexity. This increase matches the intuitive meaning of “complexity” as related to differentiation between cell types in an organism, which typically results from the interactions between multidomain regulatory processes.6 distinct directed domain combinations. And yet in the genomes analyzed here, we observed a total of only 34,778 domain combinations, which corresponds to only about 0.05% of the theoretical maximum. Therefore, we can speculate that the process of domain recombination is not entirely random and that organisms evolved some mechanisms that constrain the process of domain recombination in such a way that the chances of harmful, nonsensical arrangements are decreased. Here, we can only speculate about possible mechanisms to implement such constraints, but, for example, this could be achieved via the specific distribution of transposable elements and/or chromosomal locations of preferred recombination “hot spots.”The main result presented in this paper, namely the fact that at least 25% of all known and 75% of all recurring domain combinations have evolved independently, is less intuitive. On one hand, it is an obvious effect of the plasticity of eukaryotic genomes, with genome rearrangements constantly reshuffling existing domain combinations. On the other hand, it is interesting that this apparently random process leads to repeated reemergence of the same domain arrangements. Given that the genomes analyzed in this work contain a total of 8,023 distinct domains, it would allow the formation of about 64×10The number of times many domain combinations emerged independently is even more significant when viewed from the perspective of individual species. Over 70% of the domain combinations present in the human genome, and about 70% for all vertebrates, have evolved independently in other species at least once. This apparent discrepancy between the global and per-species averages is caused by a large number—over 22,000, unique, species-specific domain combinations, which, while rare  in individual species, add up to a large percentage over all species. One can argue that we are seeing two types of domain combinations: “universal, reemerging domain combinations” and “clade–specific, non-reemerging domain combinations.”One might speculate that domains that tend to appear in independently evolved domain combinations could be functionally different from those that make up combinations that only appeared once. This seems not to be the case, though— preliminary studies using a variety of methods and tools  indicate that there is no significant correlation between domain function and the tendency of domains to appear in independently evolved domain combinations. Similarly, strong correlation between domain “promiscuity” Drosophila melanogaster and C. elegans, to vertebrates, such as humans. The high rate of independent domain combination evolution between protostomes and deuterostomes  have unique domain combinations (combinations not shared with other branches). Due to unequal sampling, it is difficult to compare these numbers. Nevertheless, some issues are worth mentioning. While, as expected, animals have the largest number of unique domain combinations , within animals there appears to be little-to-no correlation between the number of unique domain combinations and morphological complexity. For example, mammals have ∼400 unique domain combinations from 10 genomes, whereas Arthropoda have roughly three times that number . Clearly, the number of unique domain combinations does not explain the complexity of mammals. In this context, we introduced the concept of clade core domain combinations, combinations exclusively found in each genome of a given clade. It can be argued that such clade core domain combinations provide fundamental and distinguishing functionality for the organisms of a clade. For example, animal core domain combinations are all involved in extracellular matrix/cell–cell adhesion functions and in transcription regulation functions and are thus strongly correlated with the development of multicellular organisms.In summary, our results stress a recurring theme—namely, that evolution is an exceedingly dynamic, and seemingly random, process. New domain combinations are being created and recreated throughout evolution. Each group of organisms (and probably even each organism) has their own solution, based on a partially shared set of building blocks (domains) to solve shared biochemical and regulatory needs.As more and more genomes are being sequenced, we expect the percentage of independent domain combination evolution to grow even more. In fact, we expect that, with sufficient data available, the following paradigm of evolution at the domain level will emerge. Major clades  have a relatively small set of distinguishing core domain combinations that are essential and defining for members of that clade . Outside of these hierarchical sets of core domain combinations , all domains are randomly undergoing reshuffling, and the vast majority keep reemerging and disappearing both over species space and over time, with the exception of various small sets of core domain combinations.−3 to 10−15 and/or filtering using the lists of domain-specific score cutoff values used by the Pfam database . Furthermore, we tested the effects of ignoring overlapping domains. We were unable to find a combination of these settings that would significantly change the numbers presented here and invalidate our conclusions. The preprocessing steps, the unweighted Fitch parsimony, the Dollo parsimony, and basic ancestral GO term analyses were performed by software of our own design Protein predictions for 172 completed eukaryotic genomes were downloaded from a variety of sources Click here for additional data file.Figure S2Domain gains and losses during eukaryote evolution. phyloXML (BZ2)Click here for additional data file.Figure S3Domain combination gains and losses during eukaryote evolution. phyloXML (BZ2)Click here for additional data file.Figure S4Parallel evolution of the NACHT∼Ankyrin combination between Neoptera and fungi. Tree nodes in which the domain combination in question has been inferred to be present are highlighted in green. Summary of conditions used: protein predictions as listed in (PDF)Click here for additional data file.Figure S5Parallel evolution of the Amidohydrolase∼Aspartate/ornithine carbamoyltransferase combination between Metazoa and Dictyostelium. Tree nodes in which the domain combination in question has been inferred to be present are highlighted in green. Summary of conditions used: protein predictions as listed in (PDF)Click here for additional data file.Figure S6Parallel evolution of the K Homology (KH)∼DEAD/DEAH box helicase combination between Bilateria and Micromonas. Tree nodes in which the domain combination in question has been inferred to be present are highlighted in green. Summary of conditions used: protein predictions as listed in (PDF)Click here for additional data file.Table S1Genomes analyzed.(XLS)Click here for additional data file.Table S2The 33 domain combinations present in all 172 eukaryotic genomes analyzed. This table shows the 33 domain combinations that are present in all 172 eukaryotic genomes analyzed in this work together with typical proteins in which these domain combinations appear. Summary of conditions used: protein predictions as listed in (XLS)Click here for additional data file.Table S3Domains appearing only in single-domain proteins. This table shows the 1,448 domains that appear only in single-domain proteins in the 172 genomes analyzed. Summary of conditions used: protein predictions as listed in (XLS)Click here for additional data file.Table S4Domains appearing only in multidomain proteins. This table shows the 535 domains that appear only in multidomain proteins in the 172 genomes analyzed. Summary of conditions used: protein predictions as listed in Table S1, domain models from Pfam 25.0, analyzed with HMMER 3.0, Pfam “gathering” cutoffs.(XLS)Click here for additional data file.Table S5Domain and domain combination counts in extant species. This table shows the numbers of distinct domains and domain combinations for the 172 genomes analyzed (color coded according to taxonomic groups and inversely sorted according to the number of domain combinations). The ratio (domain combinations)/(domains2) is also shown, Summary of conditions used: protein predictions as listed in (XLS)Click here for additional data file.Table S6Core and clade-specific domain and domain combination numbers. This shows the numbers of core, as well as clade- and species-specific, domains and domain combinations. Summary of conditions used: protein predictions as listed in (XLS)Click here for additional data file.Table S7Domain combinations appearing in representatives of each of the five eukaryotic supergroups analyzed. Each domain combination listed in this table appears in at least one member of each of the five eukaryotic supergroups analyzed in this work. Summary of conditions used: protein predictions as listed in (XLS)Click here for additional data file.Table S8List of core domain combinations. Summary of conditions used: protein predictions as listed in (XLS)Click here for additional data file.Table S9List of core domains. Summary of conditions used: protein predictions as listed in (XLS)Click here for additional data file.Table S10Numbers of reappearing domain combinations. Summary of conditions used: protein predictions as listed in (XLS)Click here for additional data file.Table S11List of reappearing domain combinations. Summary of conditions used: protein predictions as listed in (XLS)Click here for additional data file.Table S12Numbers of domain combinations per genome which independently evolved in a different genome at least once. Summary of conditions used: protein predictions as listed in (XLS)Click here for additional data file.


Mineral nutrition during wheat grain development has large effects on wheat flour protein content and composition, which in turn affect flour quality and immunogenic potential for a commodity of great economic value. However, it has been difficult to define the precise effects of mineral nutrition on protein composition because of the complexity of the wheat flour proteome. Recent improvements in the identification of flour proteins by tandem mass spectrometry (MS/MS) and the availability of a comprehensive proteome map of flour from the US wheat Butte 86 now make it possible to document changes in the proportions of individual flour proteins that result from the application of mineral nutrition.Triticum aestivum 'Butte 86' were grown with or without post-anthesis fertilization (PAF) and quantitative 2-dimensional gel electrophoresis (2-DE) was used to analyze protein composition of the resulting flour. Significant changes in the proportions of 54 unique proteins were observed as a result of the treatment. Most omega-gliadins, high molecular weight glutenin subunits (HMW-GS) and serpins as well as some alpha-gliadins increased in proportion with PAF. In contrast, alpha-amylase/protease inhibitors, farinins, purinins and puroindolines decreased in proportion. Decreases were also observed in several low molecular weight glutenin subunits (LMW-GS), globulins, defense proteins and enzymes. The ratio of HMW-GS to LMW-GS in the flour increased from 0.61 to 0.95 and the ratio of gliadins to glutenins increased from 1.02 to 1.30 with PAF. Because flour protein content doubled with PAF from 7 to 14%, most protein types actually increased in absolute amount (μg/mg flour protein). Data further suggest that flour proteins change with PAF according to their content of sulfur-containing amino acids Cys + Met.Plants of A 2-DE approach revealed changes in the wheat flour proteome due to PAF that are important for flour quality and immunogenic potential. The work forms a baseline for further studies of the effects of environmental variables on flour protein composition and provides clues about the regulation of specific flour protein genes. The study also is important for identifying targets for breeding programs and biotechnology efforts aimed at improving flour quality. Each year wheat farmers make strategic decisions about the amount and timing of fertilizer applications that influence yield, grain quality, and economic returns for this major world crop. Such decisions may also impact local water and air quality. One well-documented effect of fertilization with nitrogen (N) is the increase in protein content. However, this depends in a complex way upon genotype, environment, timing and type of N application -7. ThereWheat flour protein composition is complex . The majFractionation studies showed that additional N was differentially partitioned into gliadins and glutenins, which increased in amount per mg of flour, compared to an albumin/globulin fraction that did not increase -19. ProtA recent 2-DE MS/MS study of proteins in white flour from Butte 86, a US spring wheat cultivar, identified 157 distinct proteins in 233 spots that together comprised 93% of the flour protein . The 157The effects of PAF on grain yield and flour properties were measured for grain harvested at maturity Table . Bushel Total protein was extracted from white flour from grain produced with and without PAF and analyzed by quantitative 2-DE Figure . Gel patAmong the spots that increased with PAF were 13 spots identified as omega-gliadins, 11 spots identified as HMW-GS, eight spots identified as alpha-gliadins, seven spots identified as serpins, five spots identified as LMW-GS, and one spot identified as gamma-gliadin Figure . AdditioAmong the spots that decreased significantly with PAF were 19 identified as alpha-amylase/protease inhibitors, 11 as LMW-GS, six as gamma-gliadins, six as farinins, six as purinins, five minor spots identified as globulins, five minor spots identified as HMW-GS, two spots identified as beta-amylase, two spots as chitinase and two as puroindoline Figure . Single In the Dupont et al study , the samGli-D3 omega-gliadins to 161% for the Gli-B3 omega-gliadins. The Gli-B3 omega-gliadins are of particular interest because they have been associated with the serious food allergy wheat-dependent exercise-induced anaphylaxis (WDEIA). Omega-gliadins that contain single cysteine residues and are likely incorporated into the glutenin polymer (omega-gliadin Cys type TC_262777) also increased in SV from 0.5 to 1.2, a 148% change. Combined spots associated with each of the five HMW-GS sequences also increased significantly in volume. SVs for individual HMW-GS types ranged from 1.5 to 3.9 in the absence of PAF and 2.3 to 5.0 with PAF , one involved in glycolysis (triose phosphate isomerase) and one involved in defense (chitinase). Our results are more detailed and precise but are in general agreement with previous studies that distinguished among protein types based on protein fractionation, banding patterns in SDS-PAGE and retention times in RP-HPLC. Most studies separated glutenin, gliadin and albumin/globulin or amphiphilic fractions before quantifying them, as it has been difficult to distinguish among these proteins in total flour extracts. However, protein fractionation introduces a trade-off between the purity of each fraction and the amount of protein recovered. Also, a single protein may partition into more than one fraction, and environmental treatments may alter partitioning of proteins among fractions. In contrast, the present study measured the effects of PAF on individual, genetically identifiable proteins without subjecting them to fractionation and thereby provides a valuable overview of the effect of PAF on the major components of the flour.Gli-B3 omega-gliadins  and the serpins while those that decreased include the defense proteins LTP, chitinase, the alpha-amylase inhibitor WTAI-CM3, and thaumatin-like protein. Globulin-2 also has substantial similarity to known food allergens in other plants [It is notable that a number of the proteins that changed in proportion with PAF are likely food allergens. Proteins designated as food allergens in the Allergome database  that incr plants . Thus, tr plants . InteresWhen considered in terms of absolute protein amounts, it is clear that the μg protein per mg flour increased for all gluten proteins as well as for many of the other protein classes. The gliadins and glutenins have a high content of Gln and Pro and serve as efficient reservoirs for storing seed N. As the N-supply increased, the synthesis of gliadins and glutenins increased, particularly ones that were low in S. This is consistent with the observed increase in the ratio of N to S in the flour. The response of the farinins to PAF was very different from that of the major gluten proteins. The farinins have moderately high levels of Gln and Pro (31-35%) and structural similarities to the major wheat gluten proteins. Yet their absolute amounts did not increase with PAF. Instead, their response to PAF was similar to that of the high S alpha-amylase/protease inhibitors.The mechanisms by which wheat flour proteins respond to PAF are undoubtedly complex. Overall, it appeared that the response to PAF was related to the S content of the proteins with low S proteins showing the greatest increase with PAF. However, individual proteins within each class were accumulated to different levels, suggesting different basal levels of expression of the corresponding genes. Additionally, there was a differential response to PAF among individual proteins within certain classes, most notably the alpha-gliadins and LMW-GS. For the omega-gliadins, changes in protein levels are in accord with the results of transcript studies in Butte 86 ,32. In pWhile 2-DE is a powerful method for evaluating changes in flour protein profiles in response to specific treatments, the data is complex and needs to be considered on several levels. Frequently, 2-DE studies report changes in individual spots that are subsequently identified by MS/MS. This approach reveals only part of the overall picture. Recent studies indicate that the same protein sequence can be distributed among several different 2-DE spots ,36-39 anMillers and bakers encourage scientists to produce cultivars with increased stability of flour quality across years and growth environments. However, to select targets for breeding programs or biotechnology efforts it is important to first identify the genes and proteins that contribute to variability in quality. The current study used quantitative 2-DE to address the effects of PAF on the entire array of abundant flour proteins. The results indicate that omega-gliadins are very sensitive to PAF and could be a major source of environmental variability. HMW-GSs, serpins, certain alpha-gliadins and LMW-GSs also appear to contribute to this variability. The study is essential for predicting the effects of agronomic inputs on flour composition and establishes the foundation for future work aimed at deciphering the complex effects of temperature and drought on the wheat flour proteome.Triticum aestivum 'Butte 86' were grown in a climate-controlled greenhouse with 16 hr days and 8 hr nights at 24°C maximum daytime and 17°C minimum night-time temperatures [-1 Plantex fertilizer , at approximately 0.1 g each of N, P and K per pot per day. Plants were grown in 36 pots of 25 cm diameter at a density of seven plants per pot. At anthesis, pots were divided into six groups. Three sets of pots were flushed with water to remove remaining NPK and subsequently were hand-watered without fertilizer. The other three sets of pots received drip irrigation with NPK fertilization, at approximately 0.3 g each of N, P and K per pot per day. Sets with and without fertilizer were alternated spatially in the greenhouse, and pots within a set were rotated weekly. Pots were weighed daily and water added to maintain the pots at 80% of water capacity. Grain was harvested at maturity and samples were milled to white flour with a Brabender Quadrumat Junior  at the Hard Winter Wheat Quality Laboratory  and tested for mixing and baking quality as previously described [Plants of the US hard red spring wheat eratures . Prior tescribed . SubsequThree separate samples of flour from each biological replicate were extracted and analyzed by 2-DE  as described in detail previously ,40,41. B® 9.2. Cary, NC: SAS Institute Inc.). Means and standard deviations for all proteins were similar among biological replicates. Probabilities from an F-test comparing means of the two treatments were calculated, both assuming that the variances were similar enough to be pooled for both treatments (4 error degrees of freedom) or differed enough between the treatments that pooling would not be appropriate (2 error degrees of freedom). An F-test was used comparing the two error terms to determine which mean comparison test was more appropriate. A Bonferroni adjustment to the F probability was also made to account for the increased likelihood of chance significance in a large set of tests. Similar calculations were made for the sums of the SVs for specific protein sequences and specific protein types, in which the average SVs for each spot for a biological replica were summed and then these sums for the three biological replicas were used in computing the analysis of variance for each protein sequence or protein type. Appropriate calculations are shown in Additional files The experimental plan included two treatments and three biological replicas, obtained from the three sets of six individual pots for each treatment. For each of the resulting six flour samples, 2-DE was performed in triplicate. The 2-DE analysis software computed the SV for each spot as the average of the three replicate gels. These average SVs for the three biological replicates and two treatments were then subjected to analysis of variance for each spot with SAS software (SAS Institute Inc. 2009. SAS OnlineDocThe absolute amount of each protein per mg of flour was estimated by multiplying SV by total protein per mg of flour. Proportions of Cys, Met, Lys, Pro and Gln were calculated as the percentage of total amino acids in the mature proteins using published sequences from Butte 86 -30 or se2-DE: 2-dimensional gel electrophoresis; HMW-GS: high molecular weight glutenin subunit; LMW-GS: low molecular weight glutenin subunit; MS/MS: tandem mass spectrometry; N: nitrogen; NPK: nitrogen, phosphorus, potassium 1:1:1 fertilizer; PAF: post-anthesis fertilization; RP-HPLC: reverse phase-high pressure liquid chromatography; S: sulfur; SDS-PAGE: SDS polyacrylamide gel electrophoresis; SV: normalized spot volume.The authors declare that they have no competing interests.FD and SA designed the study, analyzed and interpreted the data and drafted the manuscript; CT carried out the quantitative 2-DE gel analysis; WH participated in the 2-DE gel analysis; LW advised on experimental design and performed statistical analysis and interpretation; WV provided the original MS/MS analysis that was essential to the project. All authors read and approved the manuscript.Statistical analysis for all individual 2-DE spots.Click here for fileStatistical analysis for summed spot volumes for each unique protein sequence.Click here for fileStatistical analysis for summed spot volumes for each protein class.Click here for fileProportions of key amino acids in flour protein types based on the sequences of the mature proteins.Click here for file


The bacterial SOS response is an elaborate program for DNA repair, cell cycle regulation and adaptive mutagenesis under stress conditions. Using sensitive sequence and structure analysis, combined with contextual information derived from comparative genomics and domain architectures, we identify two novel domain superfamilies in the SOS response system. We present evidence that one of these, the SOS response associated peptidase  is a novel thiol autopeptidase. Given the involvement of other autopeptidases, such as LexA and UmuD, in the SOS response, this finding suggests that multiple structurally unrelated peptidases have been recruited to this process. The second of these, the ImuB-C superfamily, is linked to the Y-family DNA polymerase-related domain in ImuB, and also occurs as a standalone protein. We present evidence using gene neighborhood analysis that both these domains function with different mutagenic polymerases in bacteria, such as Pol IV (DinB), Pol V (UmuCD) and ImuA-ImuB-DnaE2 and also other repair systems, which either deploy Ku and an ATP-dependent ligase or a SplB-like radical SAM photolyase. We suggest that the SRAP superfamily domain functions as a DNA-associated autoproteolytic switch that recruits diverse repair enzymes upon DNA damage, whereas the ImuB-C domain performs a similar function albeit in a non-catalytic fashion. We propose that C3Orf37, the eukaryotic member of the SRAP superfamily, which has been recently shown to specifically bind DNA with 5-hydroxymethylcytosine, 5-formylcytosine and 5-carboxycytosine, is a sensor for these oxidized bases generated by the TET enzymes from methylcytosine. Hence, its autoproteolytic activity might help it act as a switch that recruits DNA repair enzymes to remove these oxidized methylcytosine species as part of the DNA demethylation pathway downstream of the TET enzymes.This article was reviewed by RDS, RF and GJ. The bacterial SOS, first described by Radman about 40 years ago, is a versatile stress-induced network for DNA repair, mutagenesis, cell cycle regulation and adaptation -4. At itEscherichia coli, a second SOS-induced mutagenic module has been reported across a wide phyletic range of bacteria in the form of the ImuA-ImuB-DnaE2 module ,9,101,9,A multiple sequence alignment of the ImuB-C domain showed that it contains a highly conserved C-terminal tryptophan and at least two strongly conserved positively charged residues Figure C; howeveOur findings indicate that peptidases with at least three unrelated structural folds and catalytic mechanisms, namely, signal peptidase-like serine-peptidases (LexA and UmuD), SRAP-like thiol peptidases and zincin-like metallopeptidases linked to ImuB-C and DinB (Pfam: DUF955) have been recruited for the SOS-associated DNA damage response. Of these at least LexA, UmuD and SRAP appear to possess autopeptidase activity. Moreover, proteolysis of UvrA, DinI, and RecN by the ClpPX system, of SulA/SfiA by the HslUV system, and of RecA and RuvB by the Lon system have also been implicated in regulation of the SOS response . Thus, tBacillus phage SPBc2 and integrated prophages of proteobacteria, e.g. gi: 167582254 from Burkholderia thailandensis. Given that integrated phages respond to stress by initiating the lytic cycle [To date the RecA protein has been studied as the primary sensor and trigger of the SOS response. However, the specific control of the temporally late-acting processes with potential to introduce mutations in the genome is less understood. Identification of the SRAP and ImuB-C domains as potential players in this process raises the possibility that these are regulators of the mutagenic arms of the SOS response. By specifically sensing types of DNA damage that could stall replication, these domains could potentially facilitate the action of translesion DNA polymerases either by autoproteolytic conformational change (SRAP) or direct recruitment (ImuB-C). Their deployment could represent checkpoints that need to be passed in order for the mutagenic processes to be activated. Thus, they could be important as regulators of “evolvability” via active mutagenesis under stress conditions. The above functional proposal might also explain the presence of SRAP in lysogenic bacteriophages: for instance, it is present in the temperate The SRAP superfamily is widespread in eukaryotes  and most likely goes back to the last eukaryotic common ancestor . Multiple sequence alignments were built using MUSCLE [http://ftp.ncbi.nih.gov/blast/documents/blastclust.html). The HHpred program was used for profile-profile comparisons. Secondary structures were predicted using the JPred program [http://www.pymol.org).Iterative sequence profile and HMM searches were respectively were performed using the PSI-BLAST  and HMMSg MUSCLE  followed program . For prehttp://ftp.ncbi.nih.gov/blast/documents/blastclust.html) to identify related sequences in gene neighborhoods. Each cluster of homologous proteins was then assigned an annotation based on the domain architecture or conserved shared domain. This allowed an initial annotation of gene neigborhoods and their grouping based on conservation of neighborhood associations. This was further refined by ensuring that genes are unidirectional on the same strand of DNA and shared a putative common promoter to be counted as a single operon. If they were on opposite strands they were examined for potential bidirectional promoter sharing patterns.For each SRAP or ImuB-C gene the gene neighborhood was determined using either the PTT file (downloadable from the NCBI ftp site) or the Genbank file in the case of whole genome shot gun sequences. The neighbors of a given query gene were extracted with a preliminary cutoff of 5 genes on either side of the query. The protein sequences of all neighbors were clustered using the BLASTCLUST program .We thank the referee for the positive evaluation of this work.Minor issuesI ask the authors and the managers of Biology Direct submission system to investigate what happened to the bibliographic references in this submission. The PDF I downloaded from BD’s website contained only reference manager codes and no references. It forced me to search each reference I wanted to look at using last author name and year, a time consuming procedure I would not like to repeat.We believe there was some problem with the uploaded manuscript . We have now reformatted the revised manuscript and it should set this issue right.Considering the importance of the ImuAB-dnaE2 operon for this work, I believe it is fair to add at least one citation of the paper that first characterized these genes in Caulobacter and showed their association with DNA repair and mutagenesis  An SOS-regulated operon involved in damage-inducible mutagenesis in Caulobacter crescentus. NAR, 33(8):2603-14, PMID: 15886391).We agree this is an important paper and have cited it in the revised manuscript in all the relevant contexts.The paragraph that starts “Beyond the induction of SOS by various genotoxic stresses, it also appears to play a role” might read more clearly if rewritten like “Beyond the induction of SOS DNA-repair response by various genotoxic stresses, the SOS gene regulatory and protein interaction network also appears to play a role”.We have now modified that sentence so that it reads better.Although I have complied with it so far, I must voice against referring to the new thiol peptidase domain by the Bacillus gene name YoqW. Gene names that start with “y” are traditionally used in genome annotation to name computationally predicted genes not associated with any phenotype or as synonyms for other gene names and are based on the chromosomal map location of the gene (PMID: 9729612). Such gene names will, therefore refer to entirely different genes in different organisms, even if closely related. I would suggest renaming DUF159 to something like SOSAE for “SOS-associated enzyme” and let the standard peptidase nomenclature wait for experimental validation.We agree this is a good suggestion. Using DUF159 or YoqW do not convey the clear functional implications of these proteins and are similarly opaque in this regard. Hence we have renamed the domain as SRAP for SOS response associated peptidase.In the sentence “small domain globular domain of about 80 residues” remove the first domain”.We have corrected this in the revised manuscript.With respect to the supplement, it would be of great value if the table of genomes contexts was sorted in some meaningful order, like by taxonomy, instead of an apparently random order. Also, redundancies in these tables should be removed.We have now reorganized the supplement, which hopefully helps better navigation.In figure We have done as suggested in the revised version.The paper presented by Aravind et al describes the identification of two novel protein domain superfamilies that are part of the bacterial SOS response system. The authors use there typical broad range on analyses, including thorough protein sequence analysis, structural analysis and genomic context to provide insights into the potential function of otherwise uncharacterized protein families. The discovery of these families arose from looking at conserved proteins in operons contains sequences known to be involved in the bacterial SOS response. The first protein family described is YoqW or DUF159, and is found in bacterial and eukaryotes. Based on sequence conservation and known structures the authors present a compelling case that this is an autoproteolytic thiol peptidase.We appreciate the positive evaluation of this work.I did find the description of the conserved glutamate a little tricky to follow, as there are two prominent glutamates in the sequence logo.Indeed there are two prominent glutamates. As described in the legend, the one which is part of the catalytic triad (inferred from the structures) is specifically marked with an asterisk above it. This one is nearly absolutely conserved, whereas the other one is less conserved as can be seen in the logo.The second protein family discovered was ImuB-C, found after the Y DNA polymerase in ImuB and in isolation, reinforcing the fact it is a distinct functional unit. The authors suggest that this domain may function as part of a DNA repair system, based on the different operons that it is found in. The authors conjecture that the domain may be a DNA binding domain, given its size and lack of obvious conserved catalytic residues. I can find no evidence to disagree with this statement, but I wonder if there could not be alternative functions for this domain, such as a protein interaction module?In principle, it is possible that the ImuB-C is involved in protein-protein interaction. However, several subtle domain architectural features weigh in favor of a DNA-binding function. First, it is found in association with a wide range of mechanistically distinct DNA repair systems  but rarely if ever in any non-DNA repair related contexts. Second, it is primarily prokaryotic in its phyletic spread, and there is no evidence for the use of a common protein-interaction signal coordinating across different DNA repair systems in prokaryotes . Third, its position in the ImuB-C proteins is comparable to the DNA binding RAGNYA fold domain found in other family Y DNA polymerases.The authors conclude by describing how these protein families may function in context of the mutagenic arms of the SOS and how the homologs in eukaryotes may function. Overall, I can find no major fault with the paper from a scientific standpoint.However, the uploaded file appeared to lack a formatted set of references, and without it I cannot judge whether all citations are correct.As mentioned in the response to reviewer 1 we have remedied this in the revised version.There are several grammatical errors within the paper. For example, ‘small domain globular domain of about 80 amino acids’. I think a thorough read through of the manuscript will catch them. The spelling of authors should also be checked (uploaded MS may be wrong).We have corrected this in the revised manuscript.There are also a few sentences where the scientific meaning is vague. If something is ‘strongly co-occurs’ what does that mean? Please support with numbers. Also, how was YoqW ‘transferred’ to eukaryotes? The authors should provide indicate where the HMMER search parameters were default.The first issue has been supported with numerical data in the revised manuscript. Regarding the transfer of YoqW to the eukaryotes: The superfamily is found across all major bacterial lineages suggesting that it was likely to have been present in the bacterial common ancestor. However, it is present only in less than 10% of the archaeal genomes and that too only in the euryarchaeal lineage. In eukaryotes it is present in most major eukaryotic lineages including the basal eukaryote Trichomonas. This phyletic pattern is most consistent with it being transferred from bacteria to eukaryotes, perhaps from early bacterial symbionts. The HMMER search parameters have been included in the revised version.They should also provide the version (or date) of the NR sequence database that was used.This has been done.Is the TASS package publicly available? If it is not, I am not sure why it mentioned.It has been removed in the revised manuscript.In this paper Aravind and colleagues describe two novel components of the bacterial SOS response, the YoqW and the ImuB-C domains, identified by gene-neighborhood analysis. Sequence conservation analyses and analyses of available structures suggest that the YoqW proteins have proteolytic activity and undergo autoproteolysis. The YoqW domain may thus represent a novel type of thiol protease. This is a fascinating insight, based on sequence and structure analysis alone, and illustrates how careful sequence searches and information from structural genomics can suggest functions for uncharacterized proteins. The function of the second identified domain (ImuB-C domain) is less clear, but the authors suggest, based on genomic context analysis, that it may be involved in binding damaged DNA structures and help recruit downstream components. I find this a very nice paper, and recommend publication without hesitation.We thank the referee for the positive evaluation of this work.I only have one comment to the authors, regarding the software packages used. In the Methods section they mention an in-house collection of perl scripts (TASS package) used for the genome context analyses. Since the most important findings of this paper, the identification of the YoqW and ImuB-C domains, was based on genome context analyses, one is left wondering about the easy reproducibility of the finding, given that this is an in-house package. I noticed that in several other recent papers the authors used this package. Given that this collection of scripts was key for the most important finding of this  papers, I suggest that the authors provide this package in the supplementary information. Sharing software used to generate the data should be a trivial component of (open access!) publishing.We agree reproducibility is important; hence, provide in the supplementary information a complete set of genome contexts used in the inferences made here. We have also added a more detailed description of the procedure on the methods that can be reproduced by anyone with access to the NCBI databases and tools. Regarding the in house perl scripts the main issue is that they are not in state for general distribution because: First, they have not been documented sufficiently for this purpose. Second, they contain numerous dependencies that make them difficult to adapt across systems. Importantly, they need to be tweaked often to catch up with the ever-diverging formats within Genbank files. We also simply lack the resources to support their usability for other users. However, if a reader might still be interested they could email us for the same.The authors declare that they have no competing interests.LA, SA and LMI collected data; LA, SA and LMI analyzed the data; SA and LMI prepared the figures; LA wrote the manuscript that was read and approved by all authors.Provides access to: 1) comprehensive list of Genbank identifiers, architectures and operons of modules uncovered in this study. 2) A comprehensive set of alignments of domains reported here in text format.Click here for file


One of the suggest strategy for patients with repeated implantation failure (RIF) is zygote intrafallopian transfer (ZIFT). However, no data exist regarding to the issue of when and under which circumstances should ZIFT be offered to patients with RIF? We therefore aimed to examine whether repeated implantation failure (RIF) patients characteristics or their previous controlled ovarian hyperstimulation (COH) variables may differentiate between those who will conceive following a ZIFT cycle and those who will not.Forty seven consecutive women admitted to our IVF unit during a 7 year period, who underwent ZIFT for RIF, were included. Ovarian stimulation characteristics, number of oocytes retrieved and number and quality of zygotes/embryos transferred were assessed and compared between the ZIFT cycle and the previous IVF/ICSI cycle and between those who conceived following the ZIFT cycle and those who did not.Twelve clinical pregnancies  were recorded following the ZIFT cycle. Those who benefit from ZIFT were young patients (≤31 yrs), who underwent ≤6 cycle attempts, yielding over eight 2PN embryos with low (≤0.4) ratio of number of top-quality embryos to total 2PN embryos. Moreover, in those destined for a ZIFT cycle, only those with >7 2PN embryo should undergo a transfer of at least five 2PN embryos.Further large prospective studies are needed to identify the specific characteristics of RIF women who may benefit from ZIFT. Controlled ovarian hyperstimulation (COH) is considered a key factor in the success of in vitro fertilization-embryo transfer (IVF-ET) . Howeverrd IVF cycle attempt, with no significant decrease between the 4th to the 20th attempt [While analyzing a data from 78,325 cycles in 34,430 women registered in the Human Fertilisation and Embryology Authority data base, Templeton and Morris [In couples with repeated implantation failures (RIF)- those after failure of three cycles in which reasonably good embryos were transferred , a comprOne of the suggest strategy for patients with RIP is zygote intrafallopian transfer (ZIFT) -13. ThisPrompted by these findings, we sought to examine whether patients characteristics or previous COH variables may differentiate between those who will conceive following a ZIFT cycle and those who will not. This will aid both fertility specialists’ counseling and their patients in adjusting the appropriate treatment strategy for RIP.We reviewed the computerized files of all consecutive women admitted to our IVF unit during a 7 year period, who reached the ovum pick-up (OPU) stage. Only patients undergoing ZIFT were included. The study was approved by our institutional review board.All the usual indications for IVF/ICSI and accepted protocols for ovarian stimulations were included. The selection of type of COH protocol used was the decision of the treating physician and largely dependent on the fashion at the time. In all protocols, gonadotropins were administered in variable doses, depending on patient age and/or ovarian responsiveness in previous cycles, and further adjusted according to serum E2 levels and vaginal ultrasound measurements of follicular diameter obtained every 2 or 3 days. Routine IVF or intracytoplasmic sperm injection (ICSI) was performed, as appropriate. ZIFT was performed 24 hours after ovum pick-up (OPU), and all patients received luteal support with progesterone.Data on patient age and infertility-treatment-related variables were collected from the files. Ovarian stimulation characteristics, number of oocytes retrieved and number and quality of zygotes/embryos transferred were assessed and compared between the ZIFT cycle and the previous IVF/ICSI cycle and between those who conceived following the ZIFT cycle and those who did not. Embryos classification was based on the individual embryo scoring parameters according to pre-established definitions . A top-qResults are presented as means ± standard deviations. Differences in variables were statistically analyzed student’s t-test and chi-square test, as appropriate. Operating Characteristic (ROC) curve analysis was applied to all continuous quantitative variables. A p value of less than 0.05 was considered significant.Forty seven patients undergoing their first ZIFT cycle were evaluated. Patients underwent their 10.2 ± 2.9 IVF cycle attempts during the study cycle  and their mean age was 33.6 ± 4.9 years. The causes of infertility and the clinical characteristics of the IVF cycle which preceded the ZIFT cycle, in the all group and in those who did or did not conceive following the ZIFT cycle, are shown in Table When comparing the COH variable during the cycle preceding the ZIFT cycle, while there were no in-between group differences in the COH protocol used, the mean daily number of gonadotropin ampoules administered, peak estradiol levels, the number of oocytes retrieved, the number of TQE, or the number of embryos transferred, a trend toward a higher number of 2 pronuclei (PN) embryos was observed in those who conceived compared to those who did not , in the following ZIFT cycle. Moreover, a non-significant (p = 0.2) lower ratio of number of TQE to total 2PN embryos was observed in those who conceived .Twelve clinical pregnancies  were recorded following the ZIFT cycle, compared to none in the previous IVF cycle. However, it should be emphasized that the increased pregnancy rate in the ZIFT cycle is biased owing to the study design, which offered this approach to patients with RIF who had failed a previous IVF attempts.When comparing the COH variable during the ZIFT cycle, there were no in-between group differences Table , except Receiver Operating Characteristic curve analysis of all the continuous quantitative variables did not reach statistically significant discriminatory value Table , probablIn the present study, patients with repeated IVF failures undergoing ZIFT, demonstrated an improved outcome with reasonable clinical pregnancy rate (PR) (25.5%). Moreover, although the hitherto published data does not provide any clear discriminatory criteria to aid selecting those RIF patients who will benefit from ZIFT, according to our experience, ZIFT should be offered to those patients with up to 6 IVF cycle failures, yielding over 8 2PN embryos with ≤2 TQE and that following the COH for the ZIFT cycle obtained at least 8 2PN.Levran et al.  evaluateSince ZIFT is supposed to improve the physiological environment for the growing zygote/embryo and to offer optimal conditions for embryonic development, those who might benefit from the procedure are patients with poor in-vitro embryo development. The observation by Levran et al. , togetheIn a recently published updated data from the same group, Weissman et al.  have sumAccording to our experience, ZIFT should be offered to young RIF patients (≤31 yrs), who underwent ≤6 cycle attempts, and who achieved over eight 2PN embryos with low (≤0.4) ratio of number of TQE to total 2PN embryos in their previous IVF-ET cycle. Moreover, in those destined for a ZIFT cycle, only those with >7 2PN embryo should undergo a transfer of at least five 2PN embryos, otherwise, a trans cervical ET should be undertaken.Of notice, in contrary to Levran et al. ,10, AslaRepeated implantation failure patients who underwent ≤6 cycle attempts, yielding over eight 2PN embryos, with low (≤0.4) ratio of number of top-quality embryos to total 2PN embryos, may benefit from ZIFT. Further large prospective studies are needed to elucidate the role of this approach in patients with repeated IVF failures patients and to identify the specific characteristics of women that will aid both fertility specialists’ counseling and their patients in adjusting the appropriate infertility treatment.COH: Controlled ovarian hyperstimulation; IVF-ET: In vitro fertilization-embryo transfer; OPU: Ovum pick-up; PN: Pronuclei; RIF: Repeated implantation failures; ZIFT: Zygote intrafallopian transfer; TQE: Top-quality embryo.The authors declare that they have no competing interests.IG- Designed the study, assisted in writing the paper and edited it, proof read the paper and took part in discussions regarding the results. JL- Performed the operations, proof read the paper and took part in discussions regarding the results. GY- Performed a portion of the statistical evaluations, proof read the paper and took part in discussions regarding the results. JD- Performed the operations, proof read the paper and took part in discussions regarding the results. MB- Operated the laboratory part, proof read the paper and took part in discussions regarding the results. RO- The principal investigator, designed the study, performed the statistical evaluations, assisted in writing the paper and edited it in all its revisions. All authors read and approved the final manuscript.


Pattern recognition receptors of the immune system have key roles in the regulation of pathways after the recognition of microbial- and danger-associated molecular patterns in vertebrates. Members of NOD-like receptor (NLR) family typically function intracellularly. The NOD-like receptor family CARD domain containing 5 (NLRC5) is the largest member of this family that also contains the largest number of leucine-rich repeats (LRRs).Due to the lack of crystal structures of full-length NLRs, projects have been initiated with the aim to model certain or all members of the family, but systematic studies did not model the full-length NLRC5 due to its unique domain architecture.Our aim was to analyze the LRR sequences of NLRC5 and some NLRC5-related proteins and to build a model for the full-length human NLRC5 by homology modeling.LRR sequences of NLRC5 were aligned and were compared with the consensus pattern of ribonuclease inhibitor protein (RI)-like LRR subfamily. Two types of alternating consensus patterns previously identified for RI repeats were also found in NLRC5. A homology model for full-length human NLRC5 was prepared and, besides the closed conformation of monomeric NLRC5, a heptameric platform was also modeled for the opened conformational NLRC5 monomers.Identification of consensus patterns of leucine-rich repeat sequences helped to identify LRRs in NLRC5 and to predict their number and position within the protein. In spite of the lack of fully adequate template structures, the presence of an untypical CARD domain and unusually high number of LRRs in NLRC5, we were able to construct a homology model for both the monomeric and homo-heptameric full-length human NLRC5 protein. The innate immune system in vertebrates has pattern recognition receptor (PRR) families that trigger inflammatory pathways in response to microbes or danger signals. Both the secreted PRRs released into the extracellular space as well as the membrane-associated PRRs, like Toll-like receptors (TLRs), are responsible for the recognition of extracellular pathogen associated molecular patterns (PAMPs), while the PRRs located in the cytosol, like NOD-like receptors (NLRs), recognize PAMPs intracellularly .In humans, the NLR family contains 22 members having in common the presence of a central NACHT domain  and a C-terminal leucine-rich repeat (LRR) receptor domain with various lengths  , superhelical (SH) and LRR domains . The NAC of LRRs . Despite of LRRs , there i of LRRs  and syst of LRRs ,8 to genStructural data were downloaded from Protein Data Bank  while prhttp://polyview.cchmc.org/polyview3d.html) was used to prepare surface representation , were analyzed. We observed that exons start at position 6 of the previously showed consensus sequence of LRRs. Out of the 43 exons analyzed, seven  were found to be too short and/or did not fit the consensus pattern. These findings were confirmed by the analysis using the LRR Conservation Mapping Program , therefohttp://www.uniprot.org), 27 LRRs  was analyzed by using the IUPred web server . We founWith further analysis of the LRR consensus patterns we identified two types of consensus sequences type 1 and 2) in NLRC5  based on the exon analysis, and similarly to the 34 amino acid residue long C-terminal capping motif of RI protein   we have We have chosen to build up 43 LRRs, the largest number so far predicted, in correspondence with the study of Istomin and coworkers  and in aThe LRR domain was suggested to adopt a large helical conformation in which the leucine-rich repeats form two full circles Figure A and 3B Both N- and C-terminal cap regions are well-studied in the case of LRR-containing proteins  and in TThe domain positioning of human NLRC5 protein was predicted based on the structure of Apaf-1 protein (Apoptotic Protease-Activating factor 1) which is distantly related to NOD-like receptors . Apaf-1 Based on the crystal structure of Apaf-1 protein we have predicted a closed conformation of monomeric human NLRC5 (Met1-Ala652) Figure A using MThe small helical domain (Pro370-Pro453) of human NLRC5 (referred here as AxP domain) is located next to the NACHT domain and contains the conserved Ala404-Val405-Pro406 structural motif. The AxP domain of NLRC5 corresponds to the small helical domain (HD1) of Apaf-1  and the Apoptosome is a molecular platform which mediates the proteolytic processing of procaspases during apoptosis. The apoptosome assembly is prompted by the activation of Apaf-1 protein by its conformational changes and oligomerization . As ApafCARD domain of Apaf-1 seemed to be disordered in the crystal structure of apoptosome-procaspase-9 CARD complex . TherefoThe oligomerization is mediated by the NACHT domain of NLRC5 (Asp198-Gly369) as in case of Apaf-1 . FollowiStructure of the LRR domain of human NLRC5 was predicted in this work based on the X-ray structure of human RI protein as described above. This LRR domain (Ile688-Thr1866) was joined to the opened conformational NLRC5 (Met1-Ala652) by a linker region (Thr653-Gln687) located between the SH and LRR domains. Structure of the SH domain was completed manually by using Sybyl with the duplication of a four α-helix containing region (Gln518-Lys606) of SH domain. This duplicated part was merged into the structure as the continuation of the α-helices of the SH domain (from Leu599) and also served as a template to predict the structure of the lacking SH-LRR linker region. The predicted structure of this short region has a lower certainty, as it is expected to have very high flexibility to facilitate the rearrangement of the domains during the activation. The C-terminal end of the Thr653-Gln687 region was close to the N-terminal end of the LRR domain (Ile688-Thr1866) in its predicted spatial position, therefore these terminal amino acids were connected. A possible conformation of the SH-LRR linker region (Thr653-Gln687) was optimized by a molecular dynamics procedure. Molecular dynamics run on this linker region was followed by short energy minimization of the entire molecule without any fixed atoms to remove the unfavorable interactions. The generated structure of the monomeric full-length human NLRC5 is shown in Figure It was described that the amino acid residues (Lys121-Arg122-Arg132-Arg133-Lys134) forming the nuclear localization signal (NLS) of NLRC5 are located in the uCARD domain  (purple). With the exception of the uCARD domain, the N-terminal domains of the opened conformational human NLRC5 were modeled using the structure of the apoptosome-procaspase-9 CARD complex as template [3IYT.pdb] (orange). The uCARD domain of opened conformational NLRC5 was built up using the predicted structure of uCARD domain of closed conformational NLRC5. The LRR domain of human NLRC5 was predicted based on the X-ray structure of human ribonuclease inhibitor [1Z7X.pdb] . Some α-helices of Apaf-1 protein were completed before homology modeling using the Biopolymer module of Sybyl (brown). A possible conformation of the SH-LRR linker region was optimized after homology modeling by a molecular dynamics procedure using Sybyl (underlined). Identical (*) and similar residues (":" and ".") are indicated, using the similarity defaults of CLUSTAL X program.Click here for file


Mass spectrometric analysis shows that DSP-PP240 secreted by Sf9 cells undergoes specific cleavage at the site predicted from the N-terminal sequence of PP extracted from dentin matrix: SMQG447↓D448DPN. DSP-PP240 is cleaved after secretion by a zinc-dependent activity secreted by Sf9 cells, generating DSP430 and PP240 products that are stable in the medium. DSP-PP processing activity is constitutively secreted by Sf9 cells, but secretion is diminished 3 days after infection. Using primers corresponding to the highly conserved catalytic domain of Drosophila melanogaster tolloid , we isolated a partial cDNA for a Spodopotera frugiperda tolloid-related-1 protein (TLR1) that is 78% identical to Drosophila TLR1 but only 65% identical to Drosophila tolloid. Tlr1 mRNA decreased rapidly in Sf9 cells after baculovirus infection and was undetectable 4d after infection, paralleling the observed decrease in secretion of the DSP-PP240 processing activity after infection. Human BMP1 is more similar to Sf9 and Drosophila TLR1 than to tolloid, and Sf9 TLR1 is more similar to BMP1 than to other mammalian homologs. Recombinant human BMP1 correctly processed baculovirus-expressed DSP-PP240 in a dose-dependent manner. Together, these data suggest that the physiologically accurate cleavage of mammalian DSP-PP240 in the Sf9 cell system represents the action of a conserved processing enzyme and support the proposed role of BMP1 in processing DSP-PP in dentin matrix.Dentin sialoprotein (DSP) and phosphophoryn (PP), acidic proteins critical to dentin mineralization, are translated from a single transcript as a DSP-PP precursor that undergoes specific proteolytic processing to generate DSP and PP. The cleavage mechanism continues to be controversial, in part because of the difficulty of obtaining DSP-PP from mammalian cells and dentin matrix. We have infected Sf9 cells with a recombinant baculovirus to produce large amounts of secreted DSP-PP Dentin sialoprotein (DSP) and phosphophoryn (PP) are two major noncollagenous dentin proteins derived from a single copy of DSP-PP gene  whose expression is tightly regulated during dentinogenesis 240” to refer specifically to the shorter variant form of rat DSP-PP used in these experiments.). DSP-PP undergoes multiple post-translational modifications, including signal peptide cleavage, Asn-linked glycosylation, phosphorylation and proteolytic processing between the DSP and PP domains, to produce mature DSP and PP proteins required for dentin mineralization. Recent research on DSP-PP cleavage has focused on the identification of its initial cleavage site and the protease(s) responsible for cleavage. For example, Qin et al. reported Y438 as the major cleavage site (2001) using tryptic fragments from native, purified DSP 447↓D448447↓D448 was the cleavage site.It is believed that DSP-PP precursor proteins are the immediate translation products of DSP-PP mRNA  was not cleaved by BMP1, TLL1 or TLL2. Again, analysis of this mutant did not provide direct evidence that G447↓D448 was the cleavage site. Yamakoshi and co-workers 447↓D448 is the DSP-PP cleavage site and only Western blot analysis to substantiate the claim that BMP1 can correctly cleave DSP-PP.Other attempts to localize the initial DSP-PP cleavage site have met with limited success because of the lack of sufficient DSP-PP precursor protein available for quantitative studies. Steiglitz et al. proposed in 2004 bone morphogenetic protein-1 (BMP1) as the candidate enzyme for proteolytic cleavage of both DMP1 and DSP-PP 240 protein could be visualized with Stains-All staining and could be identified unambiguously by mass spectrometry 240 band, we proposed that the DSP-PP cleavage site was G447↓D448240 band which has permitted direct determination of the amino acid sequence of this peptide by ion trap/fragmentation MS and firmly establishes that the initial cleavage site in DSP-PP240 is G447↓D448.Previously, we used a baculovirus expression system that was capable of producing high yields of DSP-PP precursor protein. The secreted DSP-PP240 at this site occurs after secretion into the conditioned medium of Sf9 cells and that cleavage is catalyzed by an endogenous Zn-dependent proteolytic activity secreted by Sf9 cells. Secretion of this activity is suppressed by baculoviral infection. We show, furthermore, that Sf9 cells transcribe a tolloid-related-1 (TLR1) peptidase gene (Spodoptera frugiperda tlr1) and that expression of this gene is similarly suppressed by baculoviral infection. We show that the human homolog of tolloid-related-1, BMP1, can also cleave DSP-PP240 to release DSP430 and PP240.We also show that cleavage of DSP-PP240 was partially purified by the polyanion extraction procedure as previously described 6 Sf9 cells  4 days after infection with baculovirus containing the DSP-PP240 cDNA (hereafter termed DSP-PP240 virus) 2. The calcium precipitate, collected after centrifugation in an Eppendorf rotor at 12,000 rpm for 5 min at room temperature, was dissolved in 1 ml of 5% trichloroacetic acid, neutralized with 3 M Tris-HCl, pH 8.8, and re-precipitated with 1 M CaCl2. This second CaCl2 precipitate, containing recombinant DSP-PP240 and products of processing, was dissolved in 0.5 ml of 0.1 M EDTA. The dissolved sample (20 µl) was fractionated on a non-denaturing polyacrylamide gel (7.5%). PP240 protein was stained with Stains-All and analyzed by MS and MS/MS analyses as described below.PP240 band was excised, transferred to a 96-well plate, and destained. The gel samples were then subjected to reduction and alkylation and then washed, dehydrated, and digested with chymotrysin. The peptides were extracted from the gel plugs with 2% aceonitrile and 1% formic acid. The extracted peptides (30 µl) were transferred to another 96-well plate, where 5 µl of matrix (α-Cyano) was added to the sample well. The samples were then vaporized to dryness and redissolved in 5 µl of 60% aceonitrile and 0.1% trifuoroacetic acid. Peptide samples were then spotted on a MALDI-TOF/TOF target plate for MS and MS/MS analyses. MS/MS, or tandem mass spectrometry, is a mass spectrometric method in which a peptide is fragmented, and the masses of the resultant fragment ions are recorded in a spectrum. The analyses were performed using the ABI 4800 MALDI-TOF/TOF  at the Michigan Protein Consortium. Searches for homologies between the amino acid sequences obtained and those of other known proteins in GenBank™, GenPept, and SwissProt were performed using BLAST software. The Michigan Proteome Consortium provided proteomics data at the University of Michigan.7.5% non-denaturing polyacrylamide gel samples were stained with Stains-All and then PP240 virus for 3 days. A mock infection served as a control. Conditioned medium (CM) was harvested by centrifugation (500×g). CM containing DSP-PP240 precursor protein was designated “CM0–3d with viral infection” and CM from uninfected Sf9 cells was designated “CM0–3d without viral infection”.Sf9 cells cultured at 28°C in T-25 flasks in 5 ml of Grace’s medium with 10% FBS and 50 µg/ml of Gentamycin were infected with DSP-PP240 virus as described above. After three day viral infection, the conditioned medium was removed and discarded. Cells were then gently washed with 1×PBS and cultured in 5 ml of fresh Grace’s medium with10% FBS and 50 µg/ml Gentamycin for an additional 4 days (from day 3 to day 7 after infections) at 28°C. Then the CM, containing largely uncleaved DSP-PP240 precursor protein, was collected on day 7 by centrifugation (500×g) and designated CM3–7d.Sf9 cells culture and infection with DSP-PP3–7d (5 ml) from virus-infected cells was incubated with CM0–3d (5 ml) from uninfected cells for different time periods at 28°C. The CM3–7d from infected cells contained uncleaved DSP-PP240 while the CM0–3d from uninfected cells contained endogenous proteolytic activity secreted by Sf9 cells. In parallel, CM3–7d (5 ml) from virus infected cells was incubated with Grace’s medium containing 10% FBS and 50 µg/ml Gentamycin (5 ml) as a control. At each time point, 1 ml samples of mixture was processed using a standard purification protocol 240, DSP430 and PP240 are soluble but other proteins in conditioned medium are precipitated, incubated at room temperature for 2 min and then centrifuges in an Eppendorf rotor at 12,000 rpm for 5 min at room temperature. The supernatant was neutralized with one-fifth volume of 3 M Tris-HCl pH 8.8 and then precipitated by adding one-tenth volume of 1 M CaCl2 and centrifuging in an Eppendorf rotor at 12,000 rpm for 5 min at room temperature. The pellet from 1 ml medium was resuspended in 100 µl of 0.1 M EDTA. 15 µl of resuspended samples were resolved onto native PAGE as described previously 240 and the cleavage products DSP430 and PP240. Stained gels were subjected to quantitative densitometry. Because the PP240 portion of DSP-PP240 is responsible for the majority of staining by the Stains-All reagent, percentage of protein processing was defined as PP240/(PP240+ DSP-PP240).CMDrosophila melanogaster (GeneBank accession number NM_079763), Culex quinquefasciatus (GeneBank accession number XM_001861486), Aedes aegypti (GeneBank accession number XM_001653501) and Tribolium castaneum (GeneBank accession number XM_965069), and obtained consensus sequences, [i.e., QAMRHWE and IMHYA(R/K)N(T/S)) as shown in 240 virus for 3 days was extracted with TRIzol® Reagent . Using RT-PCR, tolloid-related-1 cDNA fragments were generated from this RNA preparation. After cloning into a TOPO cloning vector , candidate clones were identified by PCR and confirmed by DNA sequencing. The cDNA sequences were then used to search the NCBI non-redundant protein sequence database for homologous peptide sequences.We aligned tolloid protein sequences from 3–7d from virus infected cells (5 ml) was incubated at 28°C with an equal volume of unconditioned (fresh) Grace’s medium in the presence of 33 ng/ml or 170 ng/ml of recombinant human BMP1 or with no enzyme addition for various times from 1 h to 72 h as indicated in the corresponding figure. At each of the time points, 1 ml of mixed medium was processed as described above. 15 µl of each resuspended sample was analyzed by native PAGE, fixed and stained with Stains-All and the percentage of protein processed was determined as described above.CM240 and PP240 bands. These intensity values were then used to calculate the ratio of PP240/(DSP-PP240+PP240). Each experiment was conducted at least 2 times and in most cases 3 or more times with comparable results. Plotted PP240/(DSP-PP240+PP240) ratios expressed as a percentage, represent the mean of at least two experiments and error bars represent the standard deviation of the mean. Data were analyzed and plotted using KaleidaGraph .Stained gels were dried, scanned to produce TIFF files and NIH ImageJ was used to quantify intensity of Stains-All stained bands. The stained protein band images were converted to grayscale and inverted and rectangular areas were used to integrate the intensity of the DSP-PP240 can be expressed in Sf9 cells using a baculovirus vector and that the precursor is partially processed into stable fragments of sizes expected for the physiological products DSP430 and PP240240 that likely represented a 76 residue peptide containing the presumed N-terminal sequence of PP240. Due to its large molecular mass, it was not possible to determine the sequence of the peptide directly 240, which would be expected to produce a 34 amino acid peptide corresponding to the N-terminus of PP240 (DSP-PP240 residues 448–481) if the precursor was cleaved after G447. MS/MS analysis of this chymotryptic peptide provided the entire expected sequence: DDPNSSDESNGSDGSDDANSESAIENGNHGDASY. This finding demonstrates that baculovirus-produced recombinant PP240 protein starts with DDPN, which corresponds to the N-terminal sequence of phosphophoryn purified from dental matrix , only a small fraction of DSP-PP240 was cleaved into mature PP240  was analyzed, even larger amounts of DSP-PP240 were present than that in CM0–3d  was largely uncleaved and remained so even when incubated for an additional 3 days  CM3–7 from infected cells with medium conditioned by incubation for three days with uninfected Sf9 cells and incubated the mixture at 28°C. CM3–7d from infected cells was incubated with Grace’s medium as a control. 3–7d from infected cells with CM0–3d medium from uninfected Sf9 cells resulted in progressive cleavage of DSP-PP240 to PP240 that was roughly linear for the first 3 days of incubation and reached near completion (∼80% cleavage) after 6 days  and tolloid-related-1 (TLR1). We therefore investigated whether Sf9 cells contain tolloid-related-1 mRNA sequences. We first obtained consensus sequences by aligning tolloid sequences from Drosophila melanogaster, Culex quinquefasciatus, Aedes aegypti and Tribolium castan. Using this alignment, we designed consensus primers corresponding to the most highly conserved regions of the catalytic domains of these enzymes and performed RT-PCR on Sf9 cell mRNA. We obtained a partial cDNA sequence encoding an open reading frame with 65% peptide sequence identity to Drosophila tolloid protein (TLD) and 78% peptide sequence identity to Drosophila tolloid-related-1 protein (TLR1). Because of greater similarity to TLR1, we propose that this clone represents a partial cDNA of a Spodopteria frugiperda tlr1 mRNA. This cDNA encodes part of the astacin protease domain with the known consensus sequence HExxHxxGFxHExxRxDRD containing the zinc-binding motif, and another conserved region, SxMHY, the so-called Met-turn .Expression of the DSP-PP precursor protein is essential for normal tooth development due to requirement for PP in dental matrix mineralization. As a result, elucidating the mechanism and regulation of DSP-PP maturation is fundamental to understanding matrix formation. As shown here, baculovirus expression of DSP-PP240, isolated using TCA precipitation, neutralization, calcium precipitation, and EDTA resuspension followed by preparative native PAGE, underwent spontaneous cleavage into DSP430 and PP240 when incubated at 37°C. We considered it unlikely that a contaminating protease in gel-purified DSP-PP240 was responsible for cleavage because of the harsh, denaturing conditions used in the purification. Indeed, the low pH and chelation steps should have inactivated Zn-dependent peptidases. Regardless of these results, we have shown here that DSP-PP240 is secreted into the conditioned medium intact, where it undergoes accurate and specific processing at the physiological cleavage site by a Zn-metalloproteinase secreted by Sf9 cells to generate stable fragments that correspond to the physiological cleavage products DSP430 and PP240.Previously 240 secreted into conditioned medium in the first 3 days after viral infection (CM0–3d) to that of DSP-PP240 secreted into freshly added medium during days 3–7 after infection (CM3–7d). Surprisingly, while significant amounts of mature DSP430 and PP240 were generated by incubation of the CM0–3d sample, little, if any cleavage of DSP-PP240 occurred in the CM3–7d sample on extended incubation, suggesting that a processing enzyme secreted by Sf9 cells within the first 3 days after infection, was no longer secreted after the first three days. Using CM3–7d media, which contained stable DSP-PP240, we could test whether a processing enzyme was secreted by uninfected Sf9 cells. We were able to demonstrate that CM0–3d media from uninfected Sf9 cells contained a Zn-dependent proteolytic activity that cleaved the DSP-PP240 into DSP430 and PP240 . This is suggested by the observation that although DSP-PP