The functional annotation and evolutionary history of proteins are usually inferred from domains predicted from the genome sequences. Traditional database-based domain prediction methods cannot identify novel domains, however, and alignment-based methods, which look for recurring segments in the proteome, are computationally demanding. Here, we propose a novel genome-wide domain prediction method, SECOM. Instead of conducting all-against-all sequence alignment, SECOM first indexes all the proteins in the genome by using a hash seed function. Local similarity can thus be detected and encoded into a graph structure, in which each node represents a protein sequence and each edge weight represents the shared hash seeds between the two nodes. SECOM then formulates the domain prediction problem as an overlapping community-finding problem in this graph. A backward graph percolation algorithm that efficiently identifies the domains is proposed. We tested SECOM on five recently sequenced genomes of aquatic animals. Our tests demonstrated that SECOM was able to identify most of the known domains identified by InterProScan. When compared with the alignment-based method, SECOM showed higher sensitivity in detecting putative novel domains, while it was also three orders of magnitude faster. For example, SECOM was able to predict a novel sponge-specific domain in nucleoside-triphosphatase (NTPases). Furthermore, SECOM discovered two novel domains, likely of bacterial origin, that are taxonomically restricted to sea anemone and hydra. SECOM is an open-source program and available at  In recent years, genome sequencing projects have generated a vast amount of biological sequence data. To make use of these data, comparative analysis has often been used to induce meaningful hypotheses through discovery of conserved sequences with regulatory functions and novel genes Each protein contains domains that have unique functions and can evolve independently of the rest of the protein chain de novo (or ab-initio) methods. The template-based methods identify the similarities between a target sequence and the template sequences in a protein structure database such as Protein Data Bank (PDB) ab-initio methods can predict protein domains by taking advantage of various sequence-based features, including sequence profiles, secondary structure predictions, and correlated mutations. Those methods use computational tools, such as neural networks ab-initio domain prediction methods on multidomain proteins is still very low The prediction of protein domains has long been considered one of the most fundamental steps in deciphering the evolution and functions of proteins as well as species. Domain detection is often closely related to the determination of discrete structural folding units. Various domain prediction methods have been reported in the literature. The existing methods can be classified into two main categories All these methods have either a well-defined structural database or structure-related features as their foundations. However, structural information is available for only a very tiny fraction of the entire set of proteins. Therefore, there is an increasing need to predict novel domain-specific signatures from protein sequences. Moreover, when the proteome data are given as the input , more information can be found. Homologous analysis of the sequences is assumed to provide evolutionary, functional, and structural information. The main difference between proteome-scale and single-protein-level domain detection is that a domain is assumed to be a recurring segment of amino acids within the proteome.N is the number of proteins in the inquiry dataset and m is the maximum length of the proteins in the dataset. This is too slow for the proteome-scale domain detection problem.Various homologous search approaches have been proposed to solve this problem. The DIVCLUS program To overcome these two bottlenecks, we propose a novel genome-scale domain detection method: SECOM, a hash SEed and COMmunity searching-based domain detection method. Given all the protein sequences from a genome, SECOM efficiently identifies all the sequentially homologous regions that recur within these proteins. SECOM does not conduct all-against-all sequence comparisons. Instead, we assume that the domains of the input protein set have highly conserved segments. The highly conserved segments are not necessarily those sharing identical amino acids, however. They may be those with sequential similarities. SECOM identifies the highly conserved segments by using hash seeds as proposed in a recent study by Li et al. At the foundation of our method is the assumption that if a cluster of protein segments corresponds to the same domain, most pairs of these segments should have at least one small fragment that shares high sequential similarity; i.e., the pairs of segments share hash seeds. The cluster of segments that correspond to a domain is called a domain cluster. The outline of SECOM is illustrated in After this step, we have a many-to-many mapping between the protein sequences and the hash seeds; i.e., each protein sequence contains some hash seeds and each hash seed corresponds to a number of protein sequences. This mapping can be represented by a graph, where the nodes represent the protein sequences. Two nodes are connected if the two protein sequences share at least one hash seed. The weights of the edges are the numbers of shared seeds. Ideally, a domain is represented by a clique in this graph.However, due to mutation during evolution, same domains even in the paralogs may share no hash seed. Because of this, we aim at finding strongly connected subgraphs, instead of the cliques. Meanwhile, a protein is usually composed of different domains, which imposes the requirement that the subgraphs can have overlapping nodes and edges in our graph problem formulation. This is equivalent to the problem of finding overlapping communities in complex networks. We propose a backward clique percolation algorithm that efficiently identifies domains in the graph. In the remainder of this section, we introduce the technical details of SECOM.Li et al. proposed the idea of hash seeds n and step size one. The hash function with a large prime base is used to calculate the hash value of each fragment. The amino acid classifications proposed in N is the number of proteins in the inquiry dataset and m is the maximum length of the proteins in the dataset. Further implementation details about the hash seeds can be found in the All the protein sequences are parsed into sliding fragments of length The length of the hash seeds is short compared with the length of the domains. Thus, the protein segments that correspond to a domain are supposed to contain similar sets of hash seeds. The next step is to identify all such groups of segments. We first convert the mapping between the protein sequences and the hash seeds into an undirected graph, in which each node represents a protein sequence and each edge represents the number of shared hash seeds between the two sequences. If there are no common hash seeds between two protein sequences, there is no edge between the two nodes in the graph. Ideally, if a domain does not have mutations in the corresponding proteins, there should be a complete subgraph, i.e., a clique, with the same, high edge weights in the graph connecting those proteins together. However, due to changes during the evolution, the same domain sequence in different proteins may contain different numbers of hash seeds, or even no hash seeds. Therefore, the problem is formulated as finding all the strongly connected subgraphs in the graph. Moreover, since proteins usually contain more than one domain, a practical algorithm must be able to find the overlapping subgraphs.k-clique community as a set of nodes belonging to adjacent k-cliques, i.e., cliques with k nodes. Later, Kumpula et al. proposed a more efficient clique percolation algorithm to find the overlapping k-communities k. Their algorithm works in a sequential manner. This algorithm can detect the overlapping k-clique communities in linear time in terms of the number of k-cliques in the graph.In graph theory, a subgraph that is more highly connected than other parts of the graph is also called a community. The community-finding problem has received much attention since the seminal paper by Newman However, none of these algorithms can be directly applied to the domain finding problem. Both algorithms require the enumeration of all cliques with sizes smaller than Here, we propose a heuristic algorithm that does not enumerate all the small cliques by using the properties of the domain detection problem. First, from our protein sequence-indexing step, we extract and store all the sequences that share the same hash seeds. According to the way our graph is defined, all such sequences are connected to each other and thus form a clique. Second, the more frequently a hash seed appears, the higher the confidence assigned to this seed. Larger cliques therefore have higher confidence.k, if there is no clique with the same size, it can still be merged into a community if at least 70% of the nodes are members of the community.According to these properties, in order to avoid the chain effect caused by the 2-clique, our algorithm is designed to work in a backward manner. It first eliminates all the edges with weights smaller than a pre-defined threshold. We use two as the default value, which means that two sequences are considered to be homologous if they contain at least two common hash seeds. The algorithm then begins with the largest clique in the graph, i.e., the one that corresponds to the most frequent hash seed. If there are other cliques with the same size The overlapping communities can thus be generated through this backward clique percolation algorithm. For the percolation steps in our algorithm, the runtime is linear in terms of the number of cliques, as shown in Note that SECOM predicts the conserved regions of the domains instead of estimating the exact boundaries of the domains. To predict the boundaries, one can apply the widely used method in local alignment algorithms, which extends the aligned conserved regions in both directions until the alignment score is lower than a certain threshold. Biological features can also be extracted to enhance the prediction accuracy for boundaries. Since these are not the main focus of the paper, we leave it as a user option.To assess the ability of SECOM to identify domains, we ran SECOM on five recently sequenced non-model organism genomes including a sponge n), the threshold for merging two communities  and the alignment-based  domain detection methods. The domains identified by SECOM are first compared with the Pfam and Superfamily domains predicted by InterProScan In validating SECOM, we assumed that domain annotations by InterProScan were the “gold standard” and evaluated the ability of SECOM to reproduce the results of InterProScan. We evaluated both cluster-level and in-cluster-level performance. The cluster-level performance measures how many domain clusters are recovered, whereas the in-cluster-level performance measures how many segments in a cluster are recovered. The overall performance metrics for SECOM and DIVCLUS are presented in As we can see from We then compared SECOM with DIVCLUS on more details. As test dataset we used the sponge protein repertoire. The comparison results on the other proteomes were similar (data not shown). The sponge proteome contained 30,327 predicted protein sequences. After excluding protein sequences shorter than 20 amino acids, 30,124 sequences were used as input. In total, InterProScan identified 4,091 domain clusters, 2,627 of which contain at least two segments from the sponge protein sequences. Since both SECOM and DIVCLUS required a domain to appear at least twice in the proteome, we considered these 2,627 domains as the “gold standard”.SECOM predicted 4,919 domains for the sponge proteome, whereas DIVCLUS predicted 3,840 domains. Most of the SECOM predicted domains (90.0%) contained less than six segments with the largest domain containing 207 segments. The distribution of size of the domain clusters is shown in We further tried to evaluate the revised performance of SECOM and DIVCLUS by considering the annotations of InterProScan as unperfect. First, we removed the segments that did not share at least two hash seeds with other segments in the same cluster from the clusters of segments annotated by InterProScan. Then, when a predicted domain cluster was compared with an annotated domain cluster, the segments that shared at least two hash seeds with all the other segments in the predicted cluster were considered true positive segments. Following this, we compared the revised performance of SECOM and DIVCLUS, as shown in We also evaluated the performance of the two methods using different thresholds. The receiver operating characteristic (ROC) curves in SECOM and DIVCLUS predicted, respectively, 1,783 and 1,138 putative novel domains (domains not recovered by InterProScan). Of the 1,138 DIVCLUS predicted domains, 825 are also recovered by SECOM, with average recall and precision values of 84.4% and 96.1%, respectively. The majority of the putative novel domains are thus predicted by both SECOM and DIVCLUS.We also found 1,015 SECOM domains that were not recovered by either DIVCLUS or InterProScan. To assess whether these domains were putative novel domains or false positives, we used a validation process similar to the one used in Amphimedon queenslandica. Of the 19 proteins, 16 also have a P-loop containing nucleoside triphosphate hydrolases (PF05729) with 150±35 amino acids after the SECOM predicted domain. We performed BLAST analysis on all the protein sequences in this cluster against the NCBI NR database. For all 19 proteins, the top hits were predicted proteins in A. queenslandica and all the proteins matched only four different A. queenslandica protein IDs given the database redundancy. The top BLAST hits that were not in A. queenslandica were with proteins annotated as “NACHT, LRR and PYD domains-containing protein 10” (13 out of the 16 proteins). NACHT, LRR and PYD domains are usually present in proteins that assembled into the inflammasome once immunological cells recognize the invading pathogens To further validate the putative novel domains, we selected a domain cluster of size 19 (http://www.ncbi.nlm.nih.gov/protein/143884714?report=genbank&log=prottop&blast_rank=1&RID=DYMP8HHZ011) (http://www.ncbi.nlm.nih.gov/protein/142495124?report=genbank&log=prottop&blast_rank=1&RID=DYMSR9PC016). A BLAST search of the NCBI NR database reveals that this domain is also found in some Cnidarian and Fungal species  , indicat8HHZ011) . Like th species .With the increasing availability of new genome sequences for non-model organisms, there is an urgent need for highly efficient and effective tools to annotate and analyze genomes of species for which there is a paucity of sequencing data and functional annotation, particularly if compared to model organisms. Here, we propose SECOM, a powerful, novel tool that automatically identifies protein domains at a genome-wide scale. SECOM is based on the assumption that domains are recurring segments in protein repertoires and are more highly conserved during evolution than are those in the inter-domain regions. Here, we were able to show that these assumptions are reasonable and demonstrate that SECOM is able to infer high coverage of domains predicted by both database- and alignment-based methods.Furthermore, SECOM shows high sensitivity to detecting putative novel domains, which makes it a valuable tool for comparative genomic studies through which scientists are often searching novel taxonomically restricted proteins defined by species-specific domains or specific combinations of domains. Here, we show that SECOM is able to detect significantly more putative novel domains than DIVCLUS can and discover novel domains in proteins that are already functionally annotated by InterProScan. Using SECOM to analyze five non-model organisms, we are able to find several putative novel domains and to propose the possible origin of these by Lateral Gene Transfer from aquatic microbial communities. Note that SECOM can be used together with any other domain predictors. Given a proteome dataset, the database-based methods, such as InterProScan, can be first applied to detect known domains. The remaining protein subsequences after cutting the InterProScan domains out can then be used as inputs for SECOM, which has been demonstrated to be sensitive to detect novel domains.Finally, SECOM is several orders of magnitude faster than DIVCLUS. Note that similar to many all-against-all alignment-based domain predictors, DIVCLUS calls the Smith-Waterman algorithm as a subroutine. Thus, the speed of such methods is dominated by the alignment step. Therefore, SECOM is expected to be orders of magnitude faster than the other widely used genome-scale domain predictors and this can be very advantageous in reducing the computational time when analyzing several large genomes in parallel. As shown in Figure S1The relationship between the length of the hash seeds and the cluster-level recall and precision of SECOM on the sponge proteome.(PDF)Click here for additional data file.Figure S2The relationship between the length of the hash seeds and the in-cluster-level recall and precision of SECOM on the sponge proteome.(PDF)Click here for additional data file.Figure S3The relationship between the length of the hash seeds and the revised cluster-level recall and precision of SECOM on the sponge proteome.(PDF)Click here for additional data file.Figure S4The relationship between the length of the hash seeds and the revised in-cluster-level recall and precision of SECOM on the sponge proteome.(PDF)Click here for additional data file.Figure S5The relationship between the length of the hash seeds, and the runtime and the memory use of SECOM on the sponge proteome.(PDF)Click here for additional data file.Figure S6The relationship between the merging threshold and the cluster-level recall and precision of SECOM on the sponge proteome.(PDF)Click here for additional data file.Figure S7The relationship between the merging threshold and the in-cluster-level recall and precision of SECOM on the sponge proteome.(PDF)Click here for additional data file.Figure S8The relationship between the merging threshold and the revised cluster-level recall and precision of SECOM on the sponge proteome.(PDF)Click here for additional data file.Figure S9The relationship between the merging threshold and the revised in-cluster-level recall and precision of SECOM on the sponge proteome.(PDF)Click here for additional data file.Figure S10The relationship between the merging threshold and the runtime and the memory use of SECOM on the sponge proteome.(PDF)Click here for additional data file.Figure S11The BLAST taxonomy report for the putative novel domain that contains 29 segments.(PNG)Click here for additional data file.Figure S12The BLAST taxonomy report for the putative novel domain that contains 49 segments.(PNG)Click here for additional data file.Table S1Overall performance of SECOM and DIVCLUS on the five aquatic proteomes. The revised recall, precision and F1 score values are given in percentiles. DIV denotes DIVCLUS and SEC denotes SECOM.(TEX)Click here for additional data file.Table S2An example of a putative novel domain cluster. Of these 19 segments, 16 have a P-loop containing nucleotide triphosphate hydrolases domain (PF05729). The first column lists protein ID of the best hit for A. queenslandica. The second column lists the positions of the segments identified by SECOM on the protein sequences. The third column lists the distance of the SECOM predicted domains to the PF05729 domains. In the fourth column is the description of the top five BLAST hits that are not A. queenslandica proteins.(TEX)Click here for additional data file.Materials S1Supplemental methods.(PDF)Click here for additional data file.


Polyketide synthase (PKSs) and nonribosomal peptide synthetase (NRPSs) are large multimodular enzymes involved in biosynthesis of polyketide and peptide toxins produced by fungi. Furthermore, hybrid enzymes, in which a reducing PKS region is fused to a single NRPS module, are also responsible of the synthesis of peptide-polyketide metabolites in fungi. The genes encoding for PKSs and NRPSs have been exposed to complex evolutionary mechanisms, which have determined the great number and diversity of metabolites. In this study, we considered the most important polyketide and peptide mycotoxins and, for the first time, a phylogenetic analysis of both PKSs and NRPSs involved in their biosynthesis was assessed using two domains for each enzyme: β-ketosynthase (KS) and acyl-transferase (AT) for PKSs; adenylation (A) and condensation (C) for NRPSs. The analysis of both KS and AT domains confirmed the differentiation of the three classes of highly, partially and non-reducing PKSs. Hybrid PKS-NRPSs involved in mycotoxins biosynthesis grouped together in the phylogenetic trees of all the domains analyzed. For most mycotoxins, the corresponding biosynthetic enzymes from distinct fungal species grouped together, except for PKS and NRPS involved in ochratoxin A biosynthesis, for which an unlike process of evolution could be hypothesized in different species. Furthermore, optionally, methyltransferase domain (MeT) assists methylation of the polyketide carbon backbone during chain formation; the thioesterase (TE) domain promotes the hydrolysis of the thioester and releases the carbon chain from the enzyme using water, whereas Claisen cyclase (CYC) domain promotes the product release using an intramolecular reaction. In addition, PKSs can undergo post-assembly line modifications by O-methyl transferase, glycosylase and other enzymes [Polyketide synthase (PKSs) and non-ribosomal peptide synthetase (NRPSs) are large multimodular enzymes involved in biosynthesis of polyketide and peptide secondary metabolites produced by microorganisms, such as bacteria and fungi. In addition to natural products that display a broad range of useful activities for pharmaceutical properties, including antibiotics (penicillins) and possible anticancer (gliotoxin) and cholesterol lowering (lovastatin/compactin) agents, a consistent number of fungal derived PK and NRP metabolites present negative mycotoxic properties, such as aflatoxins, ochratoxin A (OTA), fumonisin and patulin, among the most important. These enzymes employ complimentary strategies to sequentially construct a diverse array of compounds from relatively simple carboxylic and amino acid building blocks ,2. In PK enzymes . Non-red enzymes . Unlike l-amino acid into a d-amino acid, as well as the dual/epimerization domains (E/C), which are responsible for both epimerization and condensation. Other optional domains are the reductase (R) domain, important for reducing of the final peptide, the methylation (MT) domain, which assists the N-methylation of the amide nitrogen, the cyclization (Cy) domain, for the formation of heterocyclic rings, and the oxidation (Ox) domain, usually located either downstream of the PCP domain or in the C-terminus of the A domain, which catalyzes the formation of an aromatic thiazol through oxidation of a thiazoline ring. Thioesterase domains (TE) are usually located in the final NRPS module and help the release of the final peptide from the enzyme through cyclization or hydrolysis [Fungal NRPSs are multifunctional enzymes composed of enzymatic modules used to elongate the amino acid chain. In NRPS, according to the collinearity rule, the number and the order of the modules represents the number and the order of amino acids in the final product ,9, but tdrolysis ,13,14,15drolysis . As welldrolysis ,17Hybrid peptide-polyketide metabolites, in which polyketides are fused to an amino acid by an amide bond, may be synthesized individually by NRPS and PKS without any direct functional hybridization, but eventually coupled in a hybrid final product. Alternatively, PKS is fused to a single NRPS module, which is sometimes truncated, to form a hybrid enzyme, so that, after a defined number of elongation steps, the polyketide intermediate is transferred to the NRPS module to be linked to the activated amino acid through a peptide bond . Fungal The major classes of mycotoxins derived from polyketide metabolism are among the most significant in agriculture and food industry: aflatoxins, fumonisins, ochratoxins and zearalenone. The biosynthetic pathway of some of them needs the enzymatic activity of a NRPS. Other PK-derived mycotoxins are emerging as important food and feed contaminants, such as fusaproliferin, beauvericin, enniatins and moniliformin . The genes encoding for PKSs and NRPSs are among the largest found in microbial genomes. Usually, these genes together with tailoring and regulatory genes tend to exist in biosynthetic clusters, that is, they are located at the same locus in the genome and are coexpressed . SequencThe evolutionary mechanism by which these clusters are created and maintained are unclear. Natural selection could have acted by near simultaneous relocations of genes previously distributed in the genome , by chroRecently, various phylogenetic analyses of fungal PKSs and NRPSs have been performed ,34,35,36Monascus purpureus is a NR-PKS containing a MeT domain downstream of ACP, the apparent result of domain arrangement [Aspergillus genus known to be able to produce citrinin. All of these fungal species with homologous citrinin PKSs belong to the same phylogenetic class of Eurotiomycetes suggesting a common ancestor in the evolution of citrinin NR-PKSs. However, the putative citrinin PKS found in A. fumigatus was more distant from the others, it does not contain the MeT, but an additional ACP domain, and its function has not been yet established. The second class of NR-PKSs  do not have MeT domain, suggesting that the gene encodings these PKSs diverged after the loss of the Met domain, as reported by Kroken et al. [1, AFB2, AFG1 and AFG2 being the four most abundant and with A. flavus and A. parasiticus being the most prominent producers. Aflatoxins share an analogous biosynthetic route with sterigmatocystin, the penultimate intermediate of aflatoxin, a carcinogenic polyketide produced by several fungal species in different genera. The initial step in aflatoxin and sterigmatocystin biosynthesis is the fatty acid synthase catalyzed formation of the starter unit hexanoic acid, which is then extended to norsolorinic acid by a NR-PKS in which the two previously unrecognized SAT, and PT domains were identified [Mycosphaerella pini, a fungal forest pathogen, remarkably similar in structure to versicolorin B, a precursor of both aﬂatoxin and sterigmatocystin. The PKS required for its production is unusual in that the ACP domain is present in triplicate [A. flavus and A. parasiticus (Class Eurotiomycetes) in the genus Mycosphaerella belonging to the Class Dothideomycetes leads to the potential for horizontal transfer of genes between these disparate classes of fungi, which probably evolved on the same host/substrate. The KS and AT domains are the most conservative domains of PKSs. The results of both their phylogenetic analyses, as represented in angement , but conangement . Homologn et al. . Among tentified ,39,40. Diplicate . In bothiplicate . The preA. sojae and A. oryzae. In A. sojae the PKS sequence contains a pretermination stop codon and encodes a truncated product: the KS and AT domains are present and are identical to the domains of the other producing Aspergillus species, whereas the TE domain is lacking. However, the lack of aflatoxin producing ability of A. sojae is primarily due to the truncation of the transcriptional activation of the regulatory gene AflR [A. oryzae, aflatoxin PKS displays a 99% similarity to PKSs of producing species; the nonaflatoxigenicity of this fungus is the result of several mutations in different genes of biosynthetic cluster [Cercospora nicotianae and C. coffeicola [Arthroderma otae PKS displaying only one ACP domain, were included in the same subclade of aflatoxins NR-PKSs. In the NR-PKS clade, the PKS13 involved in zearalenone biosynthesis was included, but it resulted clearly separated from the other NR-PKSs with a high bootstrap in both the domain analyzed (100% for KS and 91% for AT), evidencing a divergence in its evolutionary origin. Zearalenones are produced by several species of Fusarium and their biosynthesis involves two divergently transcribed PKS genes, sharing the same promoter and termed pks13 and pks4 (or zea1 and zea2), respectively [Cochliobolus heterostrophus, in which two HR-PKS (PKS1 and PKS2) are required to synthesize the linear carbon chain [C. heterostrophus and the homologous PKS1 of Mycosphaerella zea-maydis, necessary for the synthesis of structurally similar PM-toxin [C. heterostrophus PKSs proteins are different partly because in PKS1 a degenerate MeT domain is present, with poorly conserved motifs that likely are non-functional, considering that T-toxin molecule is not methylated [A. terreus; the two PKS (PksH and PksJ) involved in the biosynthesis of alternariol and the PKS involved in the biosynthesis of AF-toxin, both produced by Alternaria alternata; and the Aspergillus OTA related PKSs. In particular, the two HR-PKSs responsible of alternariol biosynthesis resulted highly different in AT domain and more closely related in KS domain. PksJ resulted phylogenetically related to Aspergillus OTA-PKS in both domains, while PksH is highly related to the LovF of A. terreus in KS domain and between the hybrid PKS-NRPS and fumonisins clades in AT domain. These results are in accordance with the evidence that PksH, having a likely regulatory role, shows an additional CMeT domain compared with PksJ and is located in a different gene cluster from PksJ [A. terreus [The group of aflatoxin PKSs contained also PKSs from nonaflatoxigenic ene AflR . In the  cluster . Duplicaffeicola , which wffeicola ; their bectively ,47. The on chain , and botPM-toxin , appearethylated . The clarom PksJ . In this terreus : the HR- terreus . As show1 is the most toxic fumonisin analog [F. verticillioides fumonisin gene cluster in two different A. niger genomes [2 and FB4 production and of a new B-series fumonisin FB6 in A. niger [A. niger [Aspergillus and Penicillium species. This mycotoxin is noted to be co-expressed with aflatoxin [Fusarium species, their most prominent member being fusarin C, requests a PKS-NRPS hybrid, the first hybrid identified in filamentous fungi [A. fumigatus is involved in the biosynthesis of pseurotin A [P. expansum [A. clavatus, is derived from a shorter polyketide chain and a different amino acid building block . According to both KS and AT phylogenetic analyses, the PKS-NRPS (CcsA) involved in its biosynthesis [F. heterosporum [A branch of the HR-PKS clade grouped the fumonisins PKSs with a consistent bootstrap of 100%, in both KS and AT trees. These are a mycotoxin group of great importance, as they are suspected to be carcinogenic to humans and are as consequence regulated mainly in maize-based products. To date, at least 28 fumonisins have been isolated from fungi and they can be divided into four groups A, B, C and P; in the B series, FBn analog . The HR-n analog . The sur genomes ,56 led tA. niger ,58. FromA. niger ,60. The flatoxin . The PKSus fungi , for theurotin A . Cytochaexpansum  leading ynthesis  seemed trosporum ; it formPenicillium species [et al. [P. nordicum, whose deposited partial sequence only displays KS and AT domains, was also included in the 6-MSAS clade. Ochratoxins are nephrotoxic and carcinogenic mycotoxins produced by a number of Aspergillus and Penicillium species [A. ochraceus [A. westerdijkiae [P. nordicum [A. carbonarius (http://jgi.doe.gov/carbonarius/) a putative OTA cluster was identified containing a PKS, which shows a high similarity to the predicted OTA cluster pks gene of the producing A. niger strain CBS 513.88 [A. carbonarius and A. niger and the OTA PKS of A. ochraceus were grouped together in the HR-PKS. For A. ochraceus, the sequence of a previously deposited partial PKS, overlapping the AT domain of the gene characterized by O’Callaghan et al. [A. westerdijkiae, a new species of fungus that was recently dismembered from Aspergillus ochraceus taxon, a different PKS required for biosynthesis of OTA was identified. Only its AT and KS domains were cloned and sequenced, and they resulted in being phylogenetically related to LovB PKSs in the hybrid synthetase group. Differently, the OTA PKS of P. nordicum clustered with 6-MSAS, as reported above. In a previous study, the partial sequence containing only KS and AT domains of an additional PKS (accession no. CAQ16344) had been identified in A. carbonarius, whose expression pattern showed a correlation to OTA production under permissive conditions [The clade of PR-PKSs, that comprises 6-methyl salicylic acid synthases, was highly supported by a bootstrap of 100% in both KS and AT trees. The formation of the polyketide methylsalicylic acid is the primary building block of the biosynthetic pathway of patulin, a mycotoxin produced by a number of different  species . In the  [et al. , the fun species . The molchraceus , A. westrdijkiae  and P. nnordicum . In the S 513.88 . The PKSn et al. , was connditions  and thatin vitro. FUM14 represents the first example of an NRPS-like enzyme catalyzing a C-O bond formation instead of the typical C-N bond [A. niger, a homolog of FUM 10 has been also found in relation to its capacity of fumonisin production. Regarding the phylogeny of FUM 14, its C domain grouped in a subclade together with domains from complete mono, bi and multimodular NRPSs. The evolutionary origin of the four domain NRPS complex of fumonisin biosynthesis is unknown, the phylogenetic position of FUM14 could suggest the origin from an initially complete ancestral NRPS as they clusterized all together with a bootstrap of 100% for their condensation domain. The second group of fungal secondary metabolites considered in this study is constituted by peptidic products generated by NRPSs. Fungal NRPs have been found to have a wide range of biological activities. In addition to toxins and mycotoxins involved in plant and animal pathogenesis, they also comprise antibiotics, immunosuppressant and anticancer agents, used as pharmaceuticals and compounds involved in different fungal activities, such as nutrition, growth and development, reproduction, pathogenicity and stress management. The varied modular structure of NRPSs entails complex evolutionary mechanisms at the basis of their origin, such as duplication and loss of modules or domains, gene fusion, recombination or conversion of modules or domains in the same NRPS or among different NRPSs. In this study, we performed the phylogenetic analysis of A and C domains of NRPSs and hybrid PKS-NRPSs involved in the biosynthesis of mycotoxins , with thC-N bond . In the A. fumigatus [Leptosphaeria maculans [l-serine and l-phenylalanine; for sirodesmin l-serine and l-tyrosine) are cyclized by formation of two peptide bonds. The A and C domains of NRPSs for gliotoxin and sirodesmin grouped together; with the two A domains from these NRPSs resulting more related between them than the two C domains, which appeared separated in the two major clades arose from the C domain analysis. It has been observed that A domains within a single biosynthetic pathway are often very similar to each other in spite of activating different amino acids [1 and A2 of gliotoxin NRPSs belonged to the same clade. In this respect, putative gliotoxin NRPSs in Zymoseptoria tritici and A. flavus present a truncated structure with one only A domain, which corresponded to the A2 domain of other gliotoxin NRPSs as depicted in Fusarium species and Beauveria bassiana and C1 and C3 domains contribute to the cyclization of the molecule [2 domain, but all the three domains resulted phylogenetically unrelated. However, C1 domain resulted more related to the last domain of a multimodular NRPS (HTS1) involved in the biosynthesis of HC toxin, a cyclic tetrapeptide that is a host selective fungal toxin produced by race 1 isolates of Cochliobolus carbonum [Penicillium digitatum a putative homologous was found, which displays a similar domain structure, even though with a greater number of domains apparently due to duplication events. All the A domains of these NRPSs grouped in a subclade comprising the two A domains of OTA NRPS of A. carbonarius and A. niger, the A domains of NRPSs involved in ergot alkaloids biosynthesis and the first A domain of enniatin/beauvericin NRPSs, supported by a significant bootstrap value (96%). Differently, the C domains of HC toxins were distributed along the different subclades identified by the phylogenetic analysis. The presence of homologous domains arranged in different combinations in NRPSs of various functions and fungal origin is likely due to events of recombination in the evolution of multimodular NRPSs. The clustering of NRPs portion of hybrid PKS-NRPSs in a subclade was supported by bootstrap value of 99 and 100% in A and C phylogenetic trees, respectively. However, the PKS-NRPSs sub-clade in A phylogenetic tree constituted a distinct clade clearly separated from other NRPS A domains, with respect to C phylogenetic tree, where PKS-NRPSs, although belonging to the same sub-clade, clusterized with other non-hybrid NRPSs C domain. This result sustains the hypothesis of their common origin, as evidenced also by the phylogenetic analysis of their PKS domains. In this group also the C domain of PKS LovB of lovastatin biosynthesis was present, confirming the result obtained with the analyses of its AT and KS domains and suggesting the possibility of a common ancestor with hybrid synthases, which could have lost the A and PCP domains during evolution. Gliotoxin is the main member of the epipolythiodioxopiperazine (ETP) class of natural products characterized by a disulfide bridged cyclic dipeptide. A two module NRPS, GliP, was shown to be involved in the biosynthesis in umigatus . Anothermaculans . The twono acids ; in factmolecule . From oucarbonum . HTS1 isA. carbonarius a monomodular, NRPS was demonstrated to be involved in the biosynthesis. It is constituted by a complete domain likely functional to the bound of phenylalanine and an additional A domain at the end whose role is still not clear. In addition, experimental data provided the first evidence that this enzymatic step precedes the chlorination step to form OTA, contributing to its toxicity, and that OTα is a product of hydrolysis of OTA, clarifying the order of reaction in OTA biosynthetic pathway, until then not completely elucidated [Aspergillus grouped together with the A3 domains of the two multimodular NRPSs found in the ergot alkaloids biosynthesis cluster. In P. nordicum a NRPS-like protein was reported to be responsible of OTA biosynthesis [Aspergillus OTA NRPSs and grouped in the clade separately from other NRPSs (100% bootstrap), together with other putative OTA NRPS, reported as outgroup by Bushley and Turgeon [Claviceps purpurea, as mentioned above [d-lysergic with the amino acids alanine, phenylalanine and proline. However, CPPS1 is lacking the first C domain, which is provided in trans by CPPS2. Of the two further NRPSs, CPPS3 is monomodular and CPPS4 is a copy of CPPS1 with high similarity and certainly arose by a gene duplication event. The current biosynthesis model explains the coexistence of CPPS1 and CPPS4 as a basis for the concurrent biosynthesis of ergotamine and ergocryptine, which shares the d-lysergic acid starter, but differs in the amino acid extension. NRPSs synthesizing ergot alkaloids were hypothesized to have originally evolved to function in animal pathogenesis [A. carbonarius and A. niger, was also evident between the C domain of the same OTA NRPSs and the C domains of monomodular CPPS2 and CPPS3 and the first C domains of trimodular CPPS1 and CPPS4, suggesting the sharing of a common origin. In the light of this, it is also interesting to observe that the A1 domain of Aspergillus OTA NRPS grouped with some A domains of HC toxin and that the C2 domain of trimodular CPPSs grouped with C domains of HC toxin NRPS. In our analyses, we also included some non-toxic metabolites of peptidic origin, like penicillins, important for their beneficial effects and their pharmaceutical utilization. The first step in penicillin biosynthesis is carried out by d-(l-α-aminoadipyl)-l-cysteinyl-d-valine (ACV) synthetase, which forms peptide bonds between the three precursor amino acids [Aspergillus with three complete modules plus two additional peptidyl carrier domain/condensation domain-units. Siderophores grouped as a subfamily in the A domain phylogenesis of Bushley and Turgeon [5 domain clustered separately from the other, together with the last C domain of enniatin/beauvericin NRPSs and the last domain of trimodular ergot alkaloids NRPSs, although this subclade was not supported by a valid bootstrap value.As written above, in OTA biosynthesis the chemical bound of phenylalanine to the polyketide dihydroisocoumarin structure is catalyzed by a NRPS. In ucidated . The secynthesis ; it is f Turgeon  as adenyed above ,82. The ogenesis . A similno acids . This grno acids ,85. In ono acids . Here we Turgeon ; in our http://www.ncbi.nlm.nih.gov/), Broad Institute (http://www.broadinstitute.org/) and JGI (http://genome.jgi.doe.gov/). The information about the real or putative involvement of the selected protein in the relevant mycotoxin biosynthesis was recovered from the published literature. Some non-toxic metabolites of polyketide and peptide origin were also included in the phylogenic analyses, like pigments , penicillins  and fungal NRPSs involved in the biosynthesis of intracellular siderophores (SidC) . The amino acid (aa) sequences data set of the selected PKSs, NRPSs and PKS-NRPS hybrids, known to be involved in mycotoxin biosynthesis, were derived from the online database of the NCBI (http://smart.embl-heidelberg.de/) and CDD (http://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml) bioinformatic software. Then using this bioinformatic approach the different KS and AT domains from PKSs and A and C domains from NRPSs were identified in the corresponding aminoacidic sequences. The complete list of the accession number of the downloaded sequences and of the annotated domain are summarized in 1–An and C1–Cn). A complete PKS-NRPS hybrid protein was identified on the basis of the occurrence of one complete module with C and A domains in NRPS portion and the KS and AT domains in PKS portion. The accepted common strategy for the identification of a specific type of domain is based on the use of the Profile Hidden Markov Models (pHMMs); these models are suited for the identification of motifs interrupted by segment of variable length and to characterize position-specific sequence similarities among family of proteins. In fact, collection of pHMMs for the various domains and domains families are available on database like Pfam , HMMER aMEGA version 5. The Maximum Parsimony (MP) trees were obtained using the Close-Neighbor-Interchange algorithm with search level 3 in which the initial trees were obtained with the random addition of sequences (10 replicates). Subsequently, after the preliminary phylogenetic results and the removal from the analysis of the not well supported sequences the Maximum Likelihood (ML) method was used for phylogeny construction using three different algorithms: RaxML-HPC [http://phylobench.vital-it.ch/raxml-bb/); MEGA5 [http://www.phylogeny.fr/). Bootstrapping was performed to assess the robustness of the phylogeny. The most robust approach to infer phylogenetic relationship among the four domains studied was ML analysis by using the RAxML algorithm, setting the bootstrap analysis to 1000 runs with the best scoring ML tree used for phylogenetic analysis, the number of characters were 525 for KS, 435 for AT, 542 for A and 412 for C domains, respectively. The final ML optimization Likelihood values were -24909.988807, -25353.725213, -44270.460459, -41195.965573 for KS, AT, A and C domains, respectively. Trees were drawn using NJplot [The reconstruction of a good and reliable phylogenetic tree is crucially dependent on the right protein alignment and the best substitution model used in the phylogenetic analysis of the data. All the aa sequences domain KS and AT for PKS and A and C for NRPS were aligned with MUSCLE . MEGA5 saxML-HPC  at Phylo); MEGA5 ; PhyML 3); MEGA5  at Phylog NJplot  and manuP. nordicum, which presents in its structure the A and PCP domains and lacks the C domain, and the other putative OTA, like proteins selected in the phylogenetic study of Bushley and Turgeon [Podospora asperina from Aspergillus, two fungi belonging to different taxonomic classes, was reported [The great diversity in the chemical structure of fungal mycotoxins, as well as the fact that a particular toxin may be produced by different fungal species, point out the complexity of molecular evolution that fungi have exploited for the production of these dangerous metabolites. The backbones of numerous mycotoxins are synthesized by PKSs or NRPSs and the biosynthesis of some other mycotoxins requires the activity of both the enzymes. In our study, we have performed the phylogenetic analyses of the main domains of these megasynthases involved in the biosynthesis of principal mycotoxins. Regarding PKSs, results obtained from KS and AT domains phylogenies agreed on the identification of two clades corresponding to the two classes of not-reducing and reducing PKSs. This latter clade was then divided in the two subclades of partially and highly reducing PKSs. Hybrid PKS-NRPSs were included in the major clade of HR-PKSs, supporting the hypothesis of a common ancestor. Hybrid synthetases grouped in defined subclades also in the phylogenetic trees of A and C domains of the corresponding NRPS portions, with the A domains being more supported by bootstrap values. The A domains tree allowed the differentiation of complete NRPS not only from hybrid enzymes, but also from NRPS-like proteins involved in mycotoxin biosynthesis and that are characterized by an incomplete modular structure. This group included the OTA NRPS of  Turgeon  as adeny Turgeon ,95, wherreported , suggestAspergillus and Penicillium genera. From our analyses, PKSs and NRPSs responsible for OTA production in Aspergilli appeared phylogenetically very distant from the two enzymes in P. nordicum. PKSs from A. carbonarius, A. niger and A. ochraceus/westerdijkiae were included in the HR-PKS group, even though a complete protein structure was available only for A. carbonarius and A. niger PKSs. The analysis of KS and AT domains, unique domains available for OTA PKS in P. nordicum, permitted us to classify it among PR-PKSs, close to 6-methyl salicylic acid synthases. A similar phylogenetic distance was observed for OTA NRPSs, which were structurally diverse, with the NRPS from P. nordicum lacking a C domain and grouping in a clade separate from regular NRPSs, differently from the enzymes from Aspergilli, which present a complete module plus an additional A domain. This situation could be explained by a process of convergent evolution of non-homologous gene clusters toward OTA biosynthesis rather than a separation from a common ancestor [Penicillium and Aspergillus genera point out the fact that retrieving information or activity on unknown proteins by similarity or homology to known amino-acidic sequences could lead to erroneous identification . In addet al. [Our analyses clearly evidenced and confirmed previous hypothesis on the complex evolutionary history through which these multimodular enzymes had developed and diversified, including gene duplications, modular rearrangements, potential gene loss and horizontal transfer. A better understanding of these evolution events could help to further clarify the mechanisms underlying biosynthesis of mycotoxins, to link specific metabolites with the corresponding enzymes and to discover new toxic metabolites and new toxigenic fungal species. Finally, the phylogenetic analysis of KS and AT domains evidenced with some minor exceptions the co-evolution of these two important conserved domains in PKS enzymes; unlike the A and C domains of multimodular NRPSs, which showed a divergent phylogenetic topology. In addition, especially in C domain tree, the different modules of the same NRPS resulted often phylogenetically unrelated, apart for the four C domains of siderophore, evidencing that their origin is not from duplicate event or co-evolution process, but probably is more related to their functional substrate specificity, as demonstrated by Rausch et al. . Finally


Cdk5 inhibition (roscovitine) resulted in actin-cytoskeleton disorganisation, prevention of protein co-localization and inhibition of movement. Cells expressing Cdk5 (D144N) kinase mutant, were unable to spread, migrate and form tube-like structures or sprouts, while Cdk5 wild-type over-expression showed enhanced motility and angiogenesis in vitro, which was maintained during hypoxia. Gene microarray studies demonstrated myocyte enhancer factor (MEF2C) as a substrate for Cdk5-mediated angiogenesis in vitro. MEF2C showed nuclear co-immunoprecipitation with Cdk5 and almost complete inhibition of differentiation and sprout formation following siRNA knock-down. In hypoxia, insertion of Cdk5/p25-inhibitory peptide (CIP) vector preserved and enhanced in vitro angiogenesis. These results demonstrate the existence of critical and complementary signalling pathways through Cdk5 and p35, and through which coordination is a required factor for successful angiogenesis in sustained hypoxic condition.Cyclin-dependent kinase-5 (Cdk5) is over-expressed in both neurons and microvessels in hypoxic regions of stroke tissue and has a significant pathological role following hyper-phosphorylation leading to calpain-induced cell death. Here, we have identified a critical role of Cdk5 in cytoskeleton/focal dynamics, wherein its activator, p35, redistributes along actin microfilaments of spreading cells co-localising with p Before to start the immunoprecipitaiton, cell lysate was pre-cleared suing 100 µl of sepharose-A slurry per ml of cell lysate. The reaction mixture with Histone H1 was then resolved by SDS-PAGE followed by autoradiography. Active Cdk5 would result in the appearance on autoradiography film of a signal at the size of phosphorylated histone H1. A purified active complex Cdk5/p35 expressed in Sf21 cells  served as a positive control. 2ng of the active complex was used in the assay. Immunoprecipitate using rabbit anti-goat antibody  served as negative controls.Cell lysates for immunoprecipitates and kinase assay were obtained as described for western blotting, in contrast, a modified RIPA lacking ionic detergent was used. Cdk5 was immunoprecipitated using protein A-sepharose CL-4B and incubated in vitro with Histone H1  and [γ-Silencer® control scrambled siRNAs was used as a negative control. Assay conditions were performed as recommended by the manufacturers.Knockdown of MEF2C expression was performed using Silencer® Select Pre-Designed & Validated siRNA . SiRNA delivery was performed using Lipofectamine 2000 . After three days of treatment, in selected media (EBM-2 with reduced FBS and without antibiotics), knockdown efficiency was tested via protein assay (Western Blotting) and cells used for in vitro angiogenesis analysis. Total RNA was isolated using Trizol Reagent, and purified using the RNeasy Micro Kit . The assay was performed according to the manufacturer’s instructions. Concentration and purity was determined using a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies) and RNA quality was assessed using Agilent RNA 6000 Nano Kit and 2100 Bioanalyzer platform . The expression pattern of untranfected cells and several clones from cells transfected with the empty vector or a dominant negative form of human Cdk5 were compared by microarray analysis. Microarrays and cDNA synthesis were performed following the GeneChip® WT cDNA Synthesis and amplification Kit (Affymetrix) and following the Affymetrix GeneChip® Whole Transcript (WT) Sense Target standard protocol . The arrThe fluorometric assay was performed according to the manufacturer’s instructions . Cytosolic proteins were specifically extracted without contaminations of cell membrane and lysosome proteases and preventing auto-activation of calpain during the extraction procedure according to the manufacturer’s instructions. Calpain activity was quantified using a fluorescence microplate reader BMG Labtech, USA. The fluorometric assay included a positive control of active calpain I, as well. Data were expressed as relative fluorescence units. Experiments were performed in triplicate.All data were expressed as mean ±SD (standard deviation). P values were calculated using the ANOVA one-way test using Student’s t-test for unpaired sample led by MS and followed by the Wilcoxon 2-sample test. Regression analysis was carried out according to standard methods provided by MS Excel and to SPSS version 12. Results were considered to be statistically significant at values of P <0.05.(15) pCdk5 and pThr(160)Cdk2. Cdk5 activity was estimated by measurement of histone H1 phosphorylation, one of its targets. The effect of scalar amounts of roscovitine on cell viability, cell apoptosis and proliferation were also determined. Roscovitine at the concentration of 50 µM inhibited completely Cdk5 activity ((160)Cdk2 ((R)-roscovitine is a well-recognized anti-neoplastic drug, carrying out both apoptotic  and antiactivity  and reduactivity , without160)Cdk2 . Roscovi160)Cdk2 . Cytotoxin vitro model of low oxygen tension mimicking hypoxia during stroke, wherein hBMEC were exposed to 24h of low oxygen levels (1%). Hypoxia conditions were defined on the evidence that in human hypoxic brain tissue (i.e. after subarachnoid haemorrhage) the partial pressure of brain tissue oxygen (PtiO2) decreased dramatically from the normal values of 40 mmHg [2 delivery, as previously described [Recent observations suggest that apoptosis of neurons after brain ischemia is strongly associated with Cdk5 hyper-activation mediated by its activator p25 , however 40 mmHg  to <10 m 40 mmHg . Consideescribed .In our model, the efficiency of hypoxia  was evidIn normoxia, inhibition of Cdk5 kinase activity with roscovitine, resulted in a significant loss or inability to form and maintain potentially viable capillary structures , as showCytoskeleton dynamic and focal complex organizations are crucial determinants for successful angiogenesis. We hypothesized that Cdk5 inhibition may affect the cell cyto-architecture and the observed inhibitory effects on angiogenesis in vitro may be the direct consequence of Cdk5 misplacement from actin and focal complexes. We also examined the involvement of the Cdk5 substrate, p35 in this cytoskeletal/focal organization.We found a marked and specific distribution of Cdk5, pCdk5 and p35 with F-actin in all phases of cell motility , having Inhibition of Cdk5 activity with roscovitine resulted in a total disorganisation of the actin- cytoskeleton and focal protein localization . With roTherefore, we hypothesised Cdk5/p35 to have a multipart role where Cdk5 and p35 contribute to the mechanisms inducing matrix/focal cytoskeletal stability and on the other side, in those governing actin polymerization and depolymerization, as required for cell traction and progression of cell movement. In this scenario, p35 could be the/a stimulus for F-actin fibre polymerization and polarity leading to the formation of actin/focal plaque complexes. Inhibition of Cdk5 activity or reduced p35 content, as seen during hypoxia  may reduThe chaotic in vitro organization of EC tubule branches observed in Cdk5-wt transfectants, prompted us to speculate about the interplay of Cdk5 with other pathways involved in the promotion of EC differentiation. Using an affymetrix microarray  we analyMoreover, blocking Cdk5 activity in Cdk5-DN, notably reduced MEF2C protein levels and the opposite effect was seen in Cdk5-wt . In contThe neuro-cytoprotective effect of CIP peptide has been amply demonstrated during neurotoxic stress, wherein the protection is conferred by the inhibition of Cdk5/p25 complex formation . Thus, wWe found that CIP expression  was ableCdk5 hyper-activation mediated by the cleaved p35 fragment, p25, and initiated via calpains is crucially associated with neuronal cytoskeletal derangement, neuronal apoptosis and cell death during ischemic brain insult , while aSeveral studies in animal and in vitro models have described important functions of the myogenic transcriptional effector MEF2C, a crucial pro-survival protein, during vascular development, vasculogenesis and angiogenesis ,31. TargKnockdown of MEF2C using small-interfering RNAs in Cdk5-wt, re-established the proper cellular network, whilst reducing abnormal cell migration and sprouting. In non-transfected cells MEF2C knockdown blocked almost completely the formation of neo-capillaries, suggesting that MEF2C could be an important Cdk5-signalling intermediate in brain ECs, and a key requirement for functional in vitro angiogenesis. A relationship between Cdk5 and MEF2C in angiogenesis has not been reported previously. However, Cdk5/p25 complexes have been shown to phosphorylate other members of MEF2 family (MEF2A and MEF2D), inhibiting their pro-survival activity, through a caspase-3 dependent degradation, in response to neurotoxic stress ,34, withHere, using a protein pull down assay, we were able to co-immunoprecipitate the two proteins, but whether this association may be due to a regulatory mechanism on MEF2C stability mediated by Cdk5 phosphorylation is still to be defined. Further work should investigate whether Cdk5 is acting as a direct regulator of MEF2C gene expression, perhaps via the E2F1-pRb axis ,37.Published work has demonstrated non-nuclear functions linked to Cdk5 in the regulation of cytoskeleton dynamic and motility . Thus, wIn our study, hypoxia markedly impaired in vitro angiogenesis, leading to a noticeable alteration in stress fibre cyto-structure with delocalization of p35 from these fibres. This was reflected in a marked inhibition of cell spreading and migration. These changes were associated with decreased p35 expression and a parallel increase in calpain expression and in the cleavage product p25. Notably, modulating Cdk5/p35 activation with the novel natural inhibitor of p25/Cdk5 complex, the CIP- peptide, we were able to reduce p35 cleavage to p25 and ameliorate angiogenesis during in vitro hypoxia. CIP increased recovery of cell spreading and formation of stable neo-capillaries, potentially increasing p35 localization with actin fibres and therefore the stabilization of the actin cytoskeleton. On this base, we propose that p35/cdk5 signalling elicits a specific protective role during in vitro angiogenesis and together with the observed protective action of the CIP peptide, may potentially aid in tissue remodelling after ischaemic stroke.In conclusion, our results show that the p35/Cdk5 is a pathway that is critically involved in controlling cell dynamics of brain EC. Activation of p35/Cdk5 signalling at the expense of p25-Cdk5 plays a protective role in hypoxic conditions, and positively contributes to preserve cell motility and the proper spatial and temporal control of cytoskeletal dynamics, which is essential for successful angiogenesis.Figure S1R-roscovitine selectively inhibited Cdk5 activity and tyrosine phosphorylation: (A-B) Inhibition of histone phosphorylation; (C-E) Cdk5 phosphorylation but not that of Cdk2. Each experiment was performed in triplicate.(TIF)Click here for additional data file.Figure S2R-roscovitine was not cytotoxic to hBMECs at concentrations used: (A-B) no increase in propidium Iodide inclusion was found, whilst (C-D) neither p-53 nor caspase-3 activity increased. (E) No reduction in cell number was seen in proliferation assays up until 70 µM concentration of R-roscovitine. All experiments were performed three times.(TIF)Click here for additional data file.Figure S3In vitro hypoxia induced cell damaging effects in hBMECs: (A and D) increased Propidium Iodide nuclear inclusion; (B) increased expression of Hsp70; (B-C) increased p-35 protein cleavage and more p25 expression; (E) an increase in calpain expression, and (F-G) an increase in the ratio of p25/p35. All experiments were carried out three times.(TIF)Click here for additional data file.Figure S4R-roscovitine inhibited, spreading, migration and tube formation of hBMECs: (Ai and C) R-roscovitine showed a reduced number of cells with the capacity to elongate as well as closure in a scratch wound assay (Aii and D) and form closed tube-like structures (Aiii and E). Numbers of cells attaching in cell culture plates was also significantly reduced (B). All experiments were repeated three times.(TIF)Click here for additional data file.Figure S5Gene microarray studies identified MEF2C down-regulation in Cdk5-DN mutants: (A) gene array results with Western blot confirmation of MEF2C protein down-regulation in DN mutants (B-C); (D) immunoprecipitation showing direct intracellular binding of Cdk5 with MEF2C protein and (E), double immunoflourescent labelling demonstrating MEF2C co-localization with phospho-Cdk5. All experiments were repeated three times.(TIF)Click here for additional data file.Figure S6siRNA down-regulation of MEF2C inhibited hBMEC angiogenesis and talin-p35 co-localization in spreading cells: (A-B) siRNA to MEF2C significantly inhibited hBMEC migration in the scratch wound assay; (C) double immunoflourescent labelling showed notably reduced talin-p35 protein interaction at the tips of spreading cells concomitant with reduced ability to polarise and spread. All experiments were performed three times.(TIF)Click here for additional data file.Figure S7CIP transfectants expressed higher levels of CIP peptide: (A) immunofluorescent identification of CIP-GFP cellular uptake; (B-C) CIP transfectants e.g. CIP14 and CIP 17 expressed notably more peptide.(TIF)Click here for additional data file.Figure S8Effect of CIP transfection on hBMEC wound healing: (A-B) The presence of CIP-vector inside hBMEC significantly increased wound closure/migration compared with empty vector/control cells. Experiments were repeated three times.(TIF)Click here for additional data file.Figure S9(TIF)Click here for additional data file.


The fortification of wheat flour with micronutrients is a common strategy to increase vitamin and mineral intake. While wheat flour mills are often inspected by agencies affiliated with national ministries to ensure compliance with national fortification standards, few countries use data derived from these inspections to construct an external monitoring system for use in program management and evaluation. The primary objective of this paper is to assess the performance of the external monitoring system utilized in Jordan according to the US Centers for Disease Control and Prevention’s Updated Guidelines for Evaluating Public Health Surveillance Systems. A secondary objective is to present mill monitoring results from 2009 to 2010 in order to demonstrate the data generated by the system. The review concludes that the data required for the system is representative, simple to collect, and can be collected in a flexible manner. The external monitoring system is acceptable to participating agencies and millers and is stable due to mandatory fortification legislation which provides the legal framework for external monitoring. Data on production of fortified flour and utilization of premix can be provided in a timely manner, but on-site mill monitoring and flour sample collection are more challenging due to resource constraints. The frequent collection of a small number of indicators can provide fortification program managers with timely information with which to base decisions. Jordan’s external monitoring system successfully documented the performance of each mill and the entire flour fortification program, and can serve as a model for other national fortification programs considering external monitoring approaches. QA/QC processes and tests related to fortification verify that fortification is properly implemented and identify any irregularities in the dosing and mixture of the micronutrient premix [The fortification of wheat flour with micronutrients is a common strategy to increase vitamin and mineral intake and is included as a key component in national health and nutrition strategies . As partt premix . In addit premix . This ist premix  or the gWith respect to flour fortification, the term external monitoring is used to describe factory inspection and technical auditing by the government food control unit . Externaet al. [Literature detailing the processes associated with external monitoring exists but is limited. Peña-Rosas et al.  developeet al. . Externaet al. ,6,7,8,9,et al. . As few This paper assesses the quality of Jordan’s external monitoring system and evaluates the performance of the national wheat fortification program using data collected by this system. Jordan has one of the most comprehensive wheat flour premix formulations utilized today, and based on the WHO 2009 statement on wheat and maize flour fortification, Jordan’s premix formulation contains the recommended quantities of iron, folic acid, and vitamin A for populations where the average flour consumption is 150–300 g per day . MoreoveThe objectives of this paper are (1) to assess the external monitoring approach utilized by the Jordanian government to monitor the national wheat fortification program against the CDC guidelines of evaluating surveillance systems  and (2) Mowahad wheat flour. Mowahad wheat flour has an extraction rate of 73%–78% [Mowahad [Mowahad wheat flour is the only flour subsidized by the government [Mowahad wheat flour be fortified according to national standards [The type of flour being fortified in Jordan is  73%–78%  and is t[Mowahad . As one vernment . In 2002tandards ,14.The flour fortification program in Jordan began in 2002  with iroSince 2002, the government of Jordan has purchased equipment and has begun distributing micronutrient premix at no cost to all wheat flour mills in Jordan. The total annual cost to the government for the procurement of premix distributed to millers is approximately 1.2 million Jordanian Dinar (JD)  . The Nutrition Division, along with other relevant government agencies, is responsible for setting the fortification standards, the purchase and distribution of the micronutrient premix, and the monitoring of the national food fortification program.Mowahad wheat flour, the utilization of premix, and the quantitative testing of iron in bread. These reports were compiled retrospectively and primarily to estimate the budget required for the following year’s premix purchases. As these reports were comprised of retrospective data, they could not be used to address issues of non-compliance at the mill level in real time.The Jordanian government’s fortification monitoring system is used both to assess the performance of the fortification program and to make key programmatic decisions, such as the quantity of premix to purchase for the following year. From 2006 to 2008, data on the fortification program was compiled and analyzed on an annual basis. These annual reports included information related to the production of Though the monitoring system is coordinated by the MoH’s Nutrition Division, other agencies play an active role in the external monitoring processes through the food fortification Technical Committee. Specifically, the Technical Committee is comprised of individuals from the Ministry of Industry and Trade (MIT), Jordanian Food and Drugs Administration (JFDA), provincial health inspectors, and the MoH Nutrition Division, and is responsible for preparing and reviewing food safety and fortification regulations and for conducting mill inspections.In 2009, a prospective monthly monitoring system was established to document the quality of the fortification program. This monitoring system aims to ensure the proper implementation of the flour fortification program. Though this system collects similar data and indicators as the reports generated between 2006 and 2008, its more frequent collection and analysis of the data now enables fortification program managers to address issues of compliance in real time.The system consists of five indicators derived from three key data sources from which the adequacy of the fortification of each mill is assessed. Mowahad wheat flour produced in the past month is sourced from mill production records (Indicator 1). In order to receive subsidies related to Mowahad wheat flour, mills are required to report the quantity of fortified flour produced to the MIT. As such, mills submit production reports, consisting of aggregated daily production data to the MIT via fax on a monthly basis.The quantity (metric tons) of “fortified” The approximate utilization (number of 25 kg boxes) of micronutrient premix used in the past month is sourced from premix storage logs (Indicator 2). In order to ensure that mills will have sufficient micronutrient premix with which to fortify their wheat flour, the mills provide premix utilization to the MoH via fax or e-mail. With this information, the MoH can transport additional premix supplies to each mill when required, and plan for future premix orders.From Indicators 1 and 2, the average addition rate  for the premix is calculated to determine if the mills were using the appropriate amount of premix (Indicator 3). The target for the addition rate of the micronutrient premix is 250 g per metric ton of flour. This standardized addition rate assures that appropriate concentrations of micronutrients will be added to the flour. The average addition rate establishes a mill’s average usage of premix. Indicator 4 presents the average addition rate as a percentage of the 250 g/MT target.The iron concentration of the mill’s flour is sourced from a quantitative test conducted on a composite wheat flour sample (Indicator 5). For this test, members of the Technical Committee of the food fortification program and locally-based MoH health inspectors collect between three and six flour samples from the end of a mill’s production line and from packed flour sacks as part of their routine monthly inspections. Flour samples from bakeries were also collected at times, though not systematically . The Technical Committee members and locally-based MoH health inspectors coordinate their inspections based upon their proximity to a given mill. Individual samples are between 200 and 300 g in weight, with the resulting composite sample weighing ~1 kg. As part of these inspections, staffers also confirmed that the micronutrient premix is correctly stored and that the micronutrient premix feeders were functioning properly. Flour samples are analyzed at the JFDA, the Royal Scientific Society (RSS), and Forensic Science Laboratory Department (FSLD) using atomic absorption to assess the iron concentration.The information for each mill is received by the MoH via fax or email and compiled into a standardized form. The CDC’s Updated Guidelines for Evaluating Public Health Surveillance Systems  providesetc., public health surveillance system(s) should emphasize those attributes that are most important for the objectives of the system” [The guidelines present nine general “attributes” of a public health monitoring system; namely simplicity, flexibility, data quality, acceptability, sensitivity, predictive value positive, representativeness, timeliness, and stability. According to the CDC guidelines, as monitoring systems “vary in methods, scope, purpose, objectives,  system” . With thUsing the CDC framework for evaluation of surveillance systems , variousMowahad wheat flour produced by each mill on a monthly basis by fax or e-mail. This information is submitted as part of the national subsidy scheme, and this information is shared with the MoH upon request. Data on premix utilization, sent via fax directly from the mills to the MoH, has been designed to be simple to produce. Rather than request the use of premix in kilograms, the system only requests the number of boxes of premix used in order to approximate the amount of premix used. As the quantitative testing of iron in the flour samples requires the collection of flour samples from each mill, the process is at times difficult to implement. The difficulty in collecting flour samples is due to the time required by members of the Technical Committee to travel to each mill, particularly mills that are far from Amman .The external monitoring system involves the assessment of only a few simple indicators. Collecting the data required to track these indicators on a regular basis does not require complex methods or tools. The MIT receives data on the quantity (metric tons) of i.e., sacrificing simplicity) of the entire system.With respect to the indicators collected through the monitoring system, there is only marginal flexibility, as the system focuses on the repeated collection of a few pre-established data points and is designed to be operated with minimal financial and technical requirements. Though additional indicators could be added into the monitoring system, this could not be done without increasing the complexity  contribute to good data quality. Data quality is currently limited by a lack of a database in which to compile data. A database would provide a means for automating the data review processes by simplifying the generation of key charts and tables to aid in the interpretation of data and by facilitating the tracking/summarizing of the trends over time.The quality of the data collected on quantity (metric tons) of ndations  and are According to the CDC evaluation guidelines , acceptaMowahad wheat flour in Jordan and is therefore fully representative.The monitoring system collates information from all mills that produce The system is designed to collect data on a monthly basis, and between 2009 and 2010, data collection activities were conducted at acceptable levels. It is recommended that data on the production of fortified flour and utilization of premix should be conducted monthly , as thisOne key factor which provided stability to the system is the presence of legislation mandating flour fortification . Such leOf the 13 mills currently operational in Jordan, 11 mills were equipped with micronutrient premix feeders when this monitoring system began. Two mills, Mill #12 and Mill #13, were not fortifying in 2009 and early 2010. Though Mill #12 was built in 2008, and began milling in late 2009, it did not install a micronutrient premix feeder until mid 2010. Mill #13 on the other hand was under construction during most of 2009, and was able to secure all equipment to begin fortifying in 2010. Of the 11 mills fortifying in April 2010, the monitoring system documented that when premix was available, the mills used an average of 79% of the target premix amount (250 g/MT) and had an average iron concentration of 34 ppm. Though not perfect, these results show that mills in Jordan are able to fortify close to national standards. When examining the national performance during the 16-month period, the months where the premix was not available are included in the average and set to zero. Using this approach, mills averaged 52% of the target premix amount and had an average iron concentration of 21 ppm.i.e., >32.25 PPM iron).There is not always consistency between the addition rate of premix (addition rate as % of target 250 ppm) and iron concentration in the flour samples tested (iron level PPM). For example, there are cases in which the % of target addition rate is low (<80%) and the PPM detected in the flour samples is higher than national standards . In the case of Jordan, the system both helped to identify mills that encountered technical issues with the operation of the micronutrient premix feeds and non-compliant mills. When mills experienced technical difficulties, members of the Technical Committee assisted mills to resolve the issues. In cases of non-compliance, the MoH issued government warnings detailing mill owner’s legal obligations to fortify The results highlight that a key challenge in implementing the external monitoring system is the person-power required to conduct the various tasks. While routine compilation of flour production and premix utilization data does not require substantial resources, the on-site inspection and collection of flour samples is labor intensive and costly (due to time requirements and petrol costs for visiting mills far from Amman). As all agencies involved in the Technical Committee have competing responsibilities and do not have the human or financial resources to sustain monthly collection of flour samples, less frequent collection of flour samples may be required. As such, quality control visits can be reduced from monthly to bi-monthly or quarterly. Regarding the inconsistency between the addition rate as % of target 250 ppm and iron concentration in the flour samples, the analysis of composite flour samples should, to some extent, mitigate the variability of the iron concentration observed in the final product. That said, the variability in the premix feed rate during the day can affect the iron concentration observed in the final product, particularly if composite flour samples are not made using individual samples collected over an 8-h period . Thus, aJordan provides a straight-forward case study of an external monitoring system used to assess the performance of a relatively small number of wheat flour mills (13 as of 2012) within a small geographic area. For countries where the number of mills is much greater and mills are geographically dispersed, however, an automated system may be favorable.i.e., mill-level) QA processes and QC tests related to fortification can be complemented and verified by external monitoring implemented by government health or food safety agencies. External monitoring of a small number of key indicators can provide program managers with information that is simple to collect, timely, and representative. With information provided by such an external monitoring system, decisions can be based on timely and substantiated evidence.Internal (Although there have been many reports in the peer-reviewed literature describing how to conduct household monitoring and/or impact evaluations of flour fortification programs, there is sparse literature available on how to construct an external monitoring system based on data from factory inspections and technical auditing. As the external monitoring results of a fortification program can greatly inform the design of a household monitoring survey or impact evaluation, improving the quality of and access to external monitoring data can assist evaluators of food fortification programs.Jordan’s external monitoring system successfully documented the performance of each mill and the entire flour fortification program. In addition, it shows that a simple monitoring system can be implemented and maintained by a relatively short-staffed Nutrition Division and Technical Committee and that the information captured can be easily analyzed, interpreted, and utilized in making programmatic decisions.


Furthermore, there is an unnecessary carriage return  "crystallographic ... methods".In the “…The N-terminal anchor domain of Nef is required for membrane association and localization into detergent-insoluble “lipid rafts” [77], while the central core encodes numerous protein interaction and intracellular trafficking motifs that contribute differentially to diverse Nef functions [78]. The central core domain of Nef adopts a stable tertiary fold, permitting its early characterization using both NMR and X-ray crystallographic methods . Our understanding of Nef-mediated HLA down-regulation has been significantly enhanced by the recently reported crystal structure of Nef protein in complex with the MHC-I cytoplasmic domain and the μ1 subunit of the clatherin AP1 complex [76].”The correct figure should be:


Brassica rapa genome. By sequence analysis together with MATH-domain proteins from other species, the B. rapa MATH-domain proteins can be grouped into 6 classes. Class-I protein has one or several MATH domains without any other recognizable domain; Class-II protein contains a MATH domain together with a conserved BTB  domain; Class-III protein belongs to the MATH/Filament domain family; Class-IV protein contains a MATH domain frequently combined with some other domains; Class-V protein has a relative long sequence but contains only one MATH domain; Class-VI protein is characterized by the presence of Peptidase and UBQ (Ubiquitinylation) domains together with one MATH domain. As part of our study regarding seed development of B. rapa, six genes are screened by SSH (Suppression Subtractive Hybridization) and their expression levels are analyzed in combination with seed developmental stages, and expression patterns suggested that Bra001786, Bra03578 and Bra036572 may be seed development specific genes, while Bra001787, Bra020541 and Bra040904 may be involved in seed and flower organ development. This study provides the first characterization of the MATH domain proteins in B. rapaThe MATH (meprin and TRAF-C homology) domain is a fold of seven anti-parallel β-helices involved in protein-protein interaction. Here, we report the identification and characterization of 90 MATH-domain proteins from the  C. elegans MATH proteins indicate that they might have important functions in the regulation of protein processing [Meprins are mammalian tissue-specific metalloendopeptidases of the astacin family implicated in developmental, normal and pathological processes by hydrolysing a variety of proteins . TRAF , in lower eukaryotes  and in lower metazoa (C. elegans) [Many MATH domain proteins that are found in humans -17 and melegans) .Arabidopsis belonging to 11 major families [MATH-BTB genes in rice, but also at least another 40 MATH-BTB pseudogenes [Arabidopsis thaliana homeobox gene 6) for proteasomal degradation [MATH domain containing proteins are found usually associated to a discrete set of other protein domains, including peptidases, filamin and RluA domains, broad-complex, tramtrack and brie-a-brae (BTB) domain, tripartite motif (TRIM), astacin domain and RING and Zinc finger domains . The BTBfamilies . Proteinudogenes , whereasudogenes -29. The udogenes . In addiradation .Brassicaceae-specific PSV-embedded proteins (BPEPs) have an N-terminal signal peptide and two tandem MATH domains and are localized in PSVs (protein storage vacuole), and at least one BPEP is tightly associated with the phytate contained within PSV globoids . AdditioPhylogenetic analysis of MATH domain proteins has proven helpful as a guide for genetic and molecular studies of this large family of proteins. Zapata and colleagues reported that MATH domain proteins can be divided into the USP7 family, the MATHd-only family, the MATHd/BTB family and the MATHd/Filament family in Brassica, but rice lacks the MATHd/Filament family; and the TRAF, TRIM37 and Meprin families are only found in animals . PhylogeBrassica rapa whole genome sequence [ Arabidopsis thaliana, Oryza sativa and Ostreococcus tauri [Brassica species. Here, we identified and analyzed MATH-domain proteins from sequence , togetheus tauri -37, and us tauri . Our datA. thaliana were retrieved from the TAIR Database  with the key word MATH in species database. Using the Arabidopsis thaliana sequences of MATH proteins, we performed a search in the O. sativa using the BLASTp algorithm in the NCBI browser (http:// blast.ncbi.nlm.nih.gov/Blast.cgi). Then these sequences, primarily those from A. thaliana and O. sativa, were used as queries to search Brassica Database  and Ostreococcus tauri database  by using the BLASTp and tBLASTn tools (http://blast.ncbi.nlm.nih.gov). The Expect threshold was set at 1.0 and other parameters were set at default values.Sequences of MATH domain proteins from http://ncbi.nlm.nih.gov/ Structure/cdd/wrpsb.cgi). The low-complexity filter was turned off, and the Expect value was set at 1.0 to detect short domains or regions of less conservation in this analysis. Domains were also verified and named according to the SMART database (http://smart.embl-heidelberg.de/).The protein sequences were analyzed for domain organization using NCBI-CD searches /12h dark photoperiod. Leaves were collected from 20, 30, 35 days-old plants after artificial pollination; roots, stems and flower buds were collected from blossoming plants. Total RNA was extracted using Trizol Reagent  from about 100 mg of collected plant tissue. The RNA preparation was then treated with DNaseı  for 30 min at 37°C, followed by enzyme inactivation by incubation at 65. The RT-solution with first strand cDNA was stored at -80°C [1). Conditions for the Q-PCR reactions were as follows: 95°C for 10 min; then 40 cycles of 95°C for 15 s, 60°C for 30 s, and 72°C for 30s .at -80°C . FluoresB. rapa genome  compared to 63 genes in Arabidopsis (NCBI), 36 genes in rice (NCBI), only 2 genes in O. tauri database (http://genome.jgi-psf.org) and 16 genes from different animals . There are ten chromosomes in Brassica rapa, just twice to Arabidopsis. It suggested that genes encoding MATH domain proteins duplicated or lost during chromosome duplication. Those genes disperse to all ten chromosomes in B. rapa (Table 2), except the localization of Bra029646, Bra040903 and Bra040904 are still be uncertain. Ch3 and Chr9 have much more MATH domain encoding genes than the others, and both have 16 genes (Table 2).Using BLASTp and tBLASTn bioinformatic tools, we identified 90 genes encoding different MATH-domain proteins from the  B. rapa MATH-domain proteins and group them within the established classes, we subtracted all MATH domain proteins from several species, including 63 proteins from A. thaliana, 36 proteins from O. sativa, 2 proteins from O. tauri, We also included the TRAF1~6 proteins, TRIM37, meprin A and B, SPOP and HAUSP from Human, MuBM-90, MmSPOP and MmPOZ4 from Mouse, SPOPL from Gallus gallus, BL2960 from Cryptococcus neoformans and USP7 from Drosophila melanogaster. According to the latest report, proteins encompassing MATH domains and their association with other protein domains are grouped in 8 families, and 4 families in Brassica [B.rapa were divided into 6 classes, and have not TRAF and Meprin family mumbers . The last 3 classes belong to a branches group in the tree, but had much difference in domain organization.To examine the phylogenetic relationships among2). Class-Ⅰ, including 30 MATH domain proteins, only has two tandem MATH domains except Bra001787 whose domain organization is similar to Class-Ⅲ including longer sequence and more MATH domains. But alignment results showed that Bra001787 is much similar to Class-I member (Supplement 3), and 74% amino acid identity with Bra040904, 25% and 27% sequence identities with Class-III member Bra007802 and Bra034251 which also have 4 MATH domains, respectively. Therefore, we classified it into Class-Ⅰ, suggesting that Bra001787 might originate from Bra040904 by duplication of MATH domain tandem. All the 10 members of Class-Ⅱ have MATH and BTB domain, and some also have another BACK domain in the C-terminus. Class-Ⅲ was fallen into a branch which Arabidopsis proteins had Filament domain at the C-terminus [B. rapa and Arabidopsis in NCBI and SMART. Class-Ⅳ contains 37 members, and is the largest class. Besides the MATH domains, some proteins have another pearl1-4 domain and Bra003329 has another Ribosomal domain in the C-terminus. But in this class, 35 proteins only contained one MATH domain. In rice, MATH only domain class is the largest family and contains about 50% MATH domain proteins [1) and having similar MATH domain may have some uncertain relation. Class-Ⅵ numbers are also longer than first four classes and all have MATH, UBQ and Peptidase domains. Previous researches suggested that the last 2 classes have ubiquitin proteases (UBPs) activity and may be derived from a common ancestor, but some sequences lacked the ubiquitin protease domain during evolutionary process [Additionally, we analyzed the architecture of 90 Brassica MATH domain proteins and found that they can be classified into six families based on existence of the other conserved domains combined with sequence similarity . Among those genes, Bra036572 expressed much higher in seed at 30 and 35 days than other genes, especially Bra020541. SSH libraries from 20 /30 days seed development of structed , and Braectively . ExpressBra020541 expresses in early stage of seed development. Bra001786 and Bra036572 have much similar expression pattern: the expression level increases with seed development process, reaches the top in seed at 35 days, and undetectable expression in root, stem and flower bud. Similarly, Bra03578 expresses much higher in seed than other organs, and also reaches the top in seed at 35days, suggesting that Bra001786, Bra036572 and Bra03578 are late developmental stage seed genes. Bra001787 and Bra040904 both express higher in seed at 30 days, suggesting that they may be the regulation genes at middle stage of seed development.According to expression of genes in seed development process, there are three expression patterns. 2). The BTB domain also known as the POZ (for Pox virus and Zinc finger) domain [1), and rice has more than 30 numbers. It suggested that those genes divided and evolved after speciation. Ubiquitin domain proteins (UDPs) and ubiquitin-like (UBL) domain proteins belong to a diverse group of proteins which are characterized by an integral UBQ or UBL domain. The majority of UDPs described so far are components of the ubiquitin system which is crucial for the degradation of most cellular proteins [1 and Fig. 2).MATH domains seem to be very important for the regulation of protein processing , 6, 9-13) domain , is an e) domain , 24. Pro) domain , 42. Araproteins , 44, In proteins , and so B.rapa, and conserved domain organization suggests that they might have similar function. Comparisons of sequence similarity and synteny of B. rapa and A. thaliana MATH-domain proteins revealed occurrence of recent gene duplication events (http://brassicadb.org/brad/searchSynteny.php). Bra00200, Bra006489 and Bra023700 show syntheny to AtBPM1, but the putative protein of Bra023700 has 170 aa without MATH domain, suggesting that it may shift its function during the evolution, and also fails to be clustered with others; Brao20764, Bra040233 and Bra001186 show syntheny to AtBPM2; Both Bra017053 and Bra000147 show syntheny to AtBPM3; Bra036437 show syntheny to AtBPM4; Bra 006591 and Bra020142 show syntheny to AtBPM5, but no sequence show syntheny to AtBPM6. It suggests MATH-BTB genes diploidization or triploidization or losing in B. rapa. Class-Ⅲ only has two Brassica proteins and two Arabidopsis proteins, and previous research showed that Arabidopsis proteins had FILAMENT domain, but they can’t be detected here. Ubiquitin Proteases (UBPs) are also found in plants  and in Metazoa [Previous reports have shown that Brassica MATH proteins fall into four classes , but we  Metazoa , and itsBrassica nupas [B.rapa homologous genes Bra001786, Bra001787, Bra020541, Bra036572, Bra035787 and Bra040904 are identified and all have only MATH domain and belong to Class-Ⅰ. The expression of Bra020541, homolog to EST T200139 in 20-day-old seed SSH library, Bra001786, Bra001787, Bra040904, Bra035787, homolog to EST T350008 and Bra036572, homolog to EST T350054 in 35-day-old seed SSH library [ Bra001786, Bra03578 and Bra036572 may be seed development specific genes, but Bra001787, Bra 020541 and Bra040904 may be involved in seed and flower organ development, indicating that MATH domain proteins may have common and/or separate functions during the evolution.MATH domain proteins are found as cytosolic signaling molecules in animals . Less plca nupas , here 6  library . The exp