The four Rep proteins of adeno-associated virus (AAV) orchestrate all aspects of its viral life cycle, including transcription regulation, DNA replication, virus assembly, and site-specific integration of the viral genome into the human chromosome 19. All Rep proteins share a central SF3 superfamily helicase domain. In other SF3 members this domain is sufficient to induce oligomerization. However, the helicase domain in AAV Rep proteins (i.e. Rep40/Rep52) as shown by its monomeric characteristic, is not able to mediate stable oligomerization. This observation led us to hypothesize the existence of an as yet undefined structural determinant that regulates Rep oligomerization. In this document, we described a detailed structural comparison between the helicase domains of AAV-2 Rep proteins and those of the other SF3 members. This analysis shows a major structural difference residing in the small oligomerization sub-domain (OD) of Rep helicase domain. In addition, secondary structure prediction of the linker connecting the helicase domain to the origin-binding domain (OBD) indicates the potential to form α-helices. We demonstrate that mutant Rep40 constructs containing different lengths of the linker are able to form dimers, and in the presence of ATP/ADP, larger oligomers. We further identified an aromatic linker residue (Y224) that is critical for oligomerization, establishing it as a conserved signature motif in SF3 helicases. Mutation of this residue critically affects oligomerization as well as completely abolishes the ability to produce infectious virus. Taken together, our data support a model where the linker residues preceding the helicase domain fold into an α-helix that becomes an integral part of the helicase domain and is critical for the oligomerization and function of Rep68/78 proteins through cooperative interaction with the OBD and helicase domains. Viruses have to optimize the limited size of their genomes in order to generate the proteins required for infection and replication. Several mechanisms are used to accomplish this including the use of multiple promoters and alternative splicing. These processes generate gene products with diverse functions through the combinatorial assembly of a small number of protein domains. The small genome of the adeno-associated virus has two major open reading frames that generate seven proteins, four non-structural Rep proteins and three capsid proteins. The non-structural Rep proteins share a motor domain that uses hydrolysis of ATP to generate the conformational changes that drive DNA replication, transcriptional regulation, site-specific integration and the packing of viral genome into capsids. These functions depend upon the oligomerization of Rep proteins on specific DNA sites through the cooperation of the N-terminal origin binding domain and the C-terminal helicase domain. We provide evidence that the linker that connects the two domains is an integral feature of the helicase domain and contains a conserved aromatic residue that is critical for oligomerization. This residue emerges to be a signature motif of SF3 helicases and is also present in a subset of bacterial Rep proteins that support rolling circle replication mechanism. In PV-E-hairpin . The nei-hairpin . Overall-hairpin . Most oftructure . We hypo20,w increases slightly with increasing concentrations is observed. The slight but significant increase in s and calculated molar mass is consistent with a weak and transient dimerization . The data where also fitted using the program sedphat to a monomer-dimer association were the process is in rapid exchange on the time scale of the centrifuge −3 M, which is at the upper end of detection by sedimentation velocity. Similar distributions of Rep40 (at 36 µM) in the presence of either 5 mM ATP or ADP are shown in To determine if the presence of nucleotides can induce oligomerization of Rep40 -containing the minimal helicase domain-, we carried out sedimentation velocity experiments in the presence and absence of nucleotides at different concentrations. The sedimentation velocity profiles offer a complete characterization of the number and type of oligomers in solution. The data were analyzed using the program sedfit In order to assess whether the interdomain linker connecting the OBD domain and the helicase domains contains additional regions of distinct structure that may play a role in promoting oligomerization, we first carried out secondary structure prediction analysis to determined if the linker contains additional regions of structure. The results suggest that the region from residue 215 to 224 has the potential to form an α-helix . We hypoNext, we sought to determine the minimal length of linker that is needed to promote oligomerization. We generated three additional constructs, named Rep68ΔN209, Rep68ΔN214 and Rep68ΔN219 and tested their ability to oligomerize . Our res+ domains. This finding is in good agreement with the unique characteristics of the AAV Rep nucleotide binding pocket, which, based on its open conformation together with the presence of an arginine finger predicts the nucleotide contribution to oligomerization In order to determine the contribution of ATP and ADP to the oligomerization of the extended linker Rep linker constructs, we performed sedimentation velocity studies in the presence of nucleotides. Our hypothesis was that if oligomerization reflects the functional state of these proteins, the addition of nucleotides should support and induce further oligomerization. octlink), where residues 206 to 224 were replaced with 18 residues from the Oct-1 linker and tested its ability to oligomerize. The sedimentation profile of Rep68 typically shows two populations with sedimentation coefficients of ∼3S and ∼13S  and measured its ability to oligomerize. We first analyzed the OBD domain (1–208) to determine any oligomerization up to concentrations of 1 mg/ml (43 µM). Our results show that while OBD is a monomer , the OBDWe generated a model of the Rep68ΔN214 construct using the X-ray structure of Rep40 (residues 225–490) and 9 residues of the linker (215–224) that were added as a helical extension to the N-terminus. The model of the α-helix was generated using Robetta To assess if the disruption of oligomerization observed with the Rep68Y224A mutant has any consequences on the AAV viral life cycle, we produced recombinant AAV2 particles expressing the GFP gene in presence of a helper virus containing the Y224A mutation in the Rep ORF. The cells were harvested and lysed, and the crude lysate (treated with an endonuclease) was used to infect Hela cells. Strikingly, the crude lysate from cells transfected with the mutant helper plasmid didn't contain any infectious rAAV2-GFP particles, as determined by FACS analysis of GFP positive cells . These r+ motor domain generate a helicase domain that forms stable hexamers. Constructs of SV40-LTag and PV-E1 without the OD domain fail to oligomerize + subdomain In this study we report that the interdomain linker present in the larger AAV Rep68/78 proteins is an integral part of their oligomerization interface. We showed that the linker region is in fact an extension of the OD domain of AAV Rep proteins. Our results have shown that Rep40 constructs containing either a complete or half linker have the ability to oligomerize. This effect is enhanced in presence of ATP or ADP. We hypothesized that the linker region from residues 215 to 224 forms a α-helix that is connected to the first α-helix of the SF3 helicase domain. Secondary structure prediction and modeling of the linker region supports this argument  and 8B. The critical role of residue Y224 in the overall AAV-2 viral life cycle is illustrated by the complete abolishment of production of infectious particles from AAV-2 vector constructs produced in the context of Rep carrying the Y224A mutation . This reIn agreement with our results, a recent report has shown that the presence of the linker in an AAV5 Rep40 construct induces oligomerization in presence of DNA. However, the authors concluded that the linker effect is primarily due to its interaction with DNA 19 promoter generate Rep40 and Rep52 with truncated OD domains and are thus unable to oligomerize. Both proteins play a critical role during DNA packaging into capsids; however, the mechanism of action of monomeric Rep40/52 during packaging remains elusive. Rep proteins generated from the P5 promoter, on the other hand, require the cooperative interaction of three different oligomeric interfaces produced by the OBD domain, the linker and the helicase domain. This feature potentially provides an additional dimension for the regulation of the diverse Rep activities when compared to the related proteins from SV40 and PV. We suggest that the cooperative interactions and the modulation of these interfaces – in particular in the presence of various specific DNA substrates – orchestrate the variety of functions performed by Rep68/Rep78 proteins and may thus represent a key to our understanding of the underlying mechanisms.The use of alternative gene promoters is a common mechanism to generate protein diversity and flexibility in gene expression. At the same time it allows to obtain multiple functions from a limited number of genes, thus optimizing the size of the genome. It is clear that in the case of the Rep proteins from the AAV virus, nature has generated two sets of proteins that differ primarily in their ability to oligomerize. Rep proteins obtained from the AAV P+ domain. As Rep40/52 have been demonstrated to be required for genome packaging it is feasible to address the question whether this process requires a Rep40/52–mediated dimeric DNA helicase activity by a mechanism that is as yet undiscovered or whether further oligomerization is induced by interaction with capsid proteins.Finally, our report introduces the possibility of two distinct helicase modes for the biological functions supported by AAV Rep proteins. In the context of the large Rep proteins, a complete OD domain directs the formation of stable oligomers with a DNA unwinding mode likely to resemble that of the related viral proteins SV40-Tag and E1. The small Rep proteins, however, appear to utilize an incomplete OD domain that retains Rep40/52 in a monomeric state with formation of transitional dimeric complexes required for ATP hydrolysis. It is intriguing to speculate that this unique arrangement allows AAV to utilize two distinct motor activities with a single AAAoctlink construct was generated by substitution of residues 206 to 224 of AAV2 Rep68 with the mouse Oct-1 linker residues 328–346 (GeneBank CAA49791) using the gene synthesis services from GeneScript. The sequences of all constructs were confirmed by DNA sequencing (GeneWiz).All mutant proteins were generated using the pHisRep68/15b plasmid, which contains the AAV2 Rep68 ORF subcloned in vector PET-15b (Novagen). Site-directed mutagenesis for mutants Y224A was generated using the QuickChange mutagenesis kit (Stratagene). Rep constructs with different linker extensions were generated by PCR with primers designed to encompass the particular protein region. Primers included restriction enzyme sites NdeI and XhoI, and the sequence of the TEV protease site. The Rep68 protein used in these studies contained a Cys to Ser mutation that prevented aggregation but was functionally identical to the wild type protein (data not shown). The Rep682, and kept at −80°C until use.All proteins were expressed using the pET-15b vector, expressed in E. coli BL21(DE3) cells (Novagen), and purified as described before The cross-linking reactions for Rep40 and Rep68ΔN200 were made according to an adapted protocol from Packman and Perham Hek 293T cells were triple transfected using polyethylenimine (PEI) with an AAV2 ITR-containing plasmid including the GFP gene, a helper plasmid expressing AAV2 Rep (wt or Y224A cloned from the pHisRep68Y224A/15b) and Cap, and a third construct containing the adenovirus helper functions . The presence of the Y224A mutation was confirmed by sequencing (Eurofins). After 72 h, the cells were harvested and lysed in 150 mM NaCl, 50 mM Tris at pH 8.5, followed by three freeze - thaw cycles. The lysate was treated for 30 minutes at 37°C with 150 units/ml of benzonase endonuclease (Sigma). HeLa cells were infected with increasing amounts of crude lysate, and the percentage of GFP-positive cells was determined three days post-infection.Sedimentation velocity experiments were carried out using a Beckman Optima XL-I analytical ultracentrifuge (Beckman Coulter Inc.) equipped with a four and eight-position AN-60Ti rotor. Rep protein samples were loaded in the cells, using in all cases buffer used in the final purification step. Samples in double sector cells were centrifuged at 25,000 rpm for Rep68 proteins (Rep68 and Rep68Y224A). For Rep40 and linker constructs sedimentation was performed at 40,000 rpm. In all experiments, temperature was kept at 20°C. Sedimentation profiles were recorded using UV absorption (280 nm) and interference scanning optics. For the analysis of the results the program Sedfit was used to calculate sedimentation coefficient distribution profiles using the Lamm Structures of AAV-2 Rep40 (1S9H), Bovine papillomavirus E1 protein (2GXA), Simian virus 40 T large antigen (1SVO) and plasmid pMV158 RepB (3DKY) were analyzed using the programs COOT


Autotransporters are secreted proteins that are assembled into the outer membrane of bacterial cells. The passenger domains of autotransporters are crucial for bacterial pathogenesis, with some remaining attached to the bacterial surface while others are released by proteolysis. An enigma remains as to whether autotransporters should be considered a class of secretion system, or simply a class of substrate with peculiar requirements for their secretion. We sought to establish a sensitive search protocol that could identify and characterize diverse autotransporters from bacterial genome sequence data. The new sequence analysis pipeline identified more than 1500 autotransporter sequences from diverse bacteria, including numerous species of Chlamydiales and Fusobacteria as well as all classes of Proteobacteria. Interrogation of the proteins revealed that there are numerous classes of passenger domains beyond the known proteases, adhesins and esterases. In addition the barrel-domain-a characteristic feature of autotransporters-was found to be composed from seven conserved sequence segments that can be arranged in multiple ways in the tertiary structure of the assembled autotransporter. One of these conserved motifs overlays the targeting information required for autotransporters to reach the outer membrane. Another conserved and diagnostic motif maps to the linker region between the passenger domain and barrel-domain, indicating it as an important feature in the assembly of autotransporters. We sought to derive a broad picture of the diversity within the Type Va group, and provide a bioinformatics framework that could be applied to the analysis of other prospective divisions within the secretion systems superfamily.Bacteria have an extraordinarily diverse array of protein secretion systems The Type Va group of proteins, the autotransporters, are defined by three domains: (i) a signal sequence at the N-terminus that enables targeting of the polypeptide to the inner membrane and through into the periplasm, (ii) the secreted passenger domain which encodes the effector function of each autotransporter, and (iii) the β-barrel “translocation domain”, hereafter referred to as the barrel-domain, consisting of a short α-helical linker segment and 12 β-strands that are assembled into a β-barrel in the outer membrane Escherichia coli (PDB: 3SZE) Haemophilus influenzae (PDB: 3H09) H. influenzae (PDB: 3SYJ) E. coli (PDB: 1WXR) Detailed information is available for a few autotransporters, including crystal structures of passenger domains that suggested some generalizations concerning autotransporter structure and biogenesis. In the well-studied cases, enzymatic domains are sandwiched into a highly β-rich structure, creating a long stalked β-helix that can be up to 100 kDa in size Recent experiments have challenged the two aspects of dogma that had explained a view of autotransporter biogenesis. Firstly that passenger domains are composed largely of β-helices, a fold that drives the translocation of the passenger through the β-barrel. The crystal structure of the small autotransporter EstA contains instead an α-helical passenger domain bearing no resemblance to the prototypical β-helix structure autonomous transporter”, rather than a class of substrate protein – or is there diversity in autotransporter barrel-domains? (iii) Is the small protein EstA a unique exception to the rule that autotransporter have extremely large passenger domains to drive protein translocation across the outer membrane? The answers to these questions provide a means to set the recent experimental work on a few key, model autotransporters in a general context.The amassed data from bacterial genome sequencing studies provides a rich resource from which to extract a comprehensive picture of the autotransporters. We sought bioinformatic strategies to interrogate these sequences and address questions that impact on our understanding of autotransporter biogenesis and function: (i) Is the three-part classification system  that was apparent from the 47 characterized autotransporters, sufficient to characterize all autotransporters? (ii) Does a single type of barrel-domain (i.e. “translocation-domain”) exist-as would be predicted if an autotransporter were an “We devised a hidden Markov model (HMM) strategy to predict autotransporters from genome sequence, and ultimately detected 1523 protein sequences as putative autotransporters. Cluster-based analysis of the barrel-domains of these proteins shows at least 14 types of β-barrel structures, composed from sequence motifs that define the autotransporter (Type Va) family in general. Conserved motifs define these various types of barrel-domain and the α-linker. Far from being unique, EstA is but one of many autotransporters with very small passenger domains which do not have an extensive β-structure. Conversely, the largest autotransporters detected in this study are ∼5-fold greater in size than the largest autotransporters previously reported. We find a conserved motif, the β-motif, which is common to all autotransporters and often, but not always, found as the final β-strand in the barrel-domain. The β-motif has similar characteristics to the targeting signal that sends eukaryotic β-barrel proteins to the mitochondrial outer membrane −5 as a cut-off. The E-value 10−5 was chosen because within this cut-off, the protein sequences identified (a) fall into a size distribution consistent with what is expected from the size of known autotransporters (b) have a predicted barrel-domain that matches to the Pfam “autotransporter” characteristics (pfam03797) as determined by the conserved domain architecture tool CDART We sought a new strategy based on hidden Markov models (HMMs) to identify autotransporters encoded within genome sequence data. Our aim was to develop a search strategy with ease-of-use and high-sensitivity, to detect autotransporters in diverse bacterial species. At the inception of this study, literature reports had identified 47 proteins in various classes of Proteobacteria where experimental evidence validated them as autotransporters . A HMM w−3. To increase the sensitivity of the search strategy, we sought a second filter to identify sequences that might be false-negatives in the primary search, i.e. genuine autotransporters that were missed because they have some atypical sequence characteristics. We therefore set a sufficiently low cut-off to capture this genuine autotransporter  using a second HMM to detect the presence of autotransporter barrel-domains in the sequences from within this set. To construct this second HMM, barrel-domain sequences were extracted from the 47 known autotransporters  represent sequences which have 100% sequence identity to other sequences in these genomes. As our strategy reports only non-redundant outcomes, these three were not present in the twin-HMM output. The final sequence  appears to be an example of a false-negative outcome from the twin-HMM search: functional analysis of UpaH concluded that this is an autotransporter, but that the genome sequence for E. coli CFT073 in this region was misassembled during genome closure To test this hypothesis we took advantage of a focused study Citrobacter rodentium (ICC168) as a bench-mark dataset. Citrobacter rodentium is a mouse pathogen used as a model of the human pathogen enteropathogenic E. coli (EPEC) because both bacteria cause similar attaching/effacing lesions and share other aspects of pathogenesis C. rodentium ICC168 has been comprehensively analysed for virulence factors and protein secretion systems based on BLAST search analysis, and 20 autotransporters were reported and catalogued C. rodentium ICC168 identified the other 19 autotransporters  is encoded in the genome of in Bordetella bronchiseptica RB50. Both of these proteins are predicted to have short, proline-rich passenger-domains and both have signal sequences as predicted by SignalP 3.0. When analyzing only the barrel-domains, these proteins are highly similar (82% sequence identity) to the tracheal colonization factor TcfA found in strains of Bordetella pertussis. The passenger domain of tracheal colonization factor is distinct from the shorter proteins  which encodes 19 putative autotransporters: only five represent proteins that were known in E. coli : the remaining fourteen are orphan proteins without obvious sequence identity to proteins of known function or characterized passenger domain structures  the SPATEs and SPATE-like proteases and (ii) a hydrolase group in which some are proteases. Based on the few proteins studied so far, the relationship between the serine protease autotransporters of the Enterobacteriaceae (SPATEs) and the SPATE-like proteases, which are equivalent autotransporters found in species that are not members of the family Enterobacteriaceae, has been noted previously C. rodentium  ShigellaFourthly, another major grouping of passenger domains evident in Bordetella pertussis is required for serum resistance in this pathogen Fifthly, the BrkA autotransporter from Helicobacter pylori , the β-motif was confined to the last β-strand  and the et alE. coli and Neisseria meningitidis, including PhoE, OmpC/OmpF, OmpT, Tsx, FadL, PorA and PorB. In these sequences they identified C-terminal residues that were crucial for binding to the BAM complex, prior to these proteins being assembled into the outer membrane MEME analysis showed that this β-motif is also found in other groups of outer membrane proteins. Robert i.e. that it had the smallest passenger domain observed in an autotransporter and the passenger domain has an α-helical structure, EstA nonetheless includes a segment corresponding to the α-linker motif  common to species of Campylobacter.While not a surprise, there is evidence of both horizontal gene transfer and gene duplication. For example, in  evident , providiPassenger-domain and barrel-domain sequences occur with a “mix-and-match” pattern in our cluster analyses; this is in keeping with a past observation in EHEC EH41 (O113:H21) where a common barrel-domain is attached to EspP, EpeA, and EspI e.g. Fibronectin; The highly repetitive β-strand structure of many autotransporter passenger domains autonomous-transport, wherein the barrel-domain serves as the translocation pore for passenger domain secretion, is that a functionally conserved type of barrel would be present in all autotransporters. Using the broad diversity of sequences identified in this study, we discovered six enriched sequence motifs in the barrel-domain, and a seventh sequence motif defining the α-linker region, which are together diagnostic of autotransporters. However, the specific arrangement of these motifs defined at least 14 broad “classes” of autotransporter barrel. The striping pattern of six motifs was found to be quite distinct around the assembled barrel, and these positions did not correlate to a type of passenger domain, or to the size of the passenger domain.A prediction of the model for One hypothesis is that the conserved sequence features represent segments of the barrel-domain that are bound by factors prior to assembly of the barrel into the outer membrane. This would explain why the order of the motifs within the domain is not important. Recently, several factors representing a targeting and assembly pathway for autotransporters have been identified. For example, SurA interacts with the barrel domain of autotransporters to assist their trafficking to the outer membrane et alIn a previous study of diverse beta-barrel proteins, Robert per se. Finding the α-linker motif in so many autotransporters that are not cleaved casts serious doubt on the suggestion that the primary function of the α-linker is to directly promote the cleavage reaction. While the crystal structure of EstA In addition to providing targeting motifs, a further prospect is that one or more motifs in the barrel-domain represent a sequence feature that interacts with the conserved α-linker segment, to help form a “proto-barrel”, a pre-assembly conformation of the barrel. The most critical difference between autotransporters and other β-barrel proteins targeted by SurA to the BAM complex is the need to ensure that the linker peptide will engage with the inner surface of what will ultimately become a folded β-barrel. Mutations within the α-linker prevent correct assembly, such that the passenger-domain of autotransporter Tsh remains in the periplasm while the barrel-domain is inserted into the outer membrane http://www.ncbi.nlm.nih.gov/protein).Forty-seven protein sequences were selected from the literature on known autotransporters. The list of autotransporters selected is presented in http://www.cbs.dtu.dk/services/SignalP/) http://bioinf.cs.ucl.ac.uk/dompred) Signal sequence lengths were predicted using SignalP 3.0 (http://hmmer.janelia.org/) as previously described An autotransporter HMM was built with HMMER (ftp://ftp.ncbi.nih.gov/genomes/Bacteria/) was used for HMM analysis. The database consisted of 1331 chromosomal and 927 plasmid files. For each species the taxonomy lineage and total number of proteins encoded were extracted from GenBank files.NCBI-Genome/Bacteria database . As described in the text, an E-value cut-off of 10−5 captured all of the sequences annotated as autotransporters, but did not detect the small autotransporter EstA. Therefore, a secondary search was undertaken after building a HMM of beta-barrel regions of AT47 (henceforth referred to as AT47-bb-HMM). For all hits detected at the E-value cut-off of 10−2 in stage 1, sequences were extracted corresponding to the C-terminal 294 amino acid residues (dataset-2), as this was the length of the largest predicted beta-barrel in the sequences in the AT47 group. AT47-bb-HMM was then used to scan dataset-2, using a cut-off value 10−2.The bacterial genome sequence data was scanned using AT47-HMM with HMMER. The scan was carried out with three cut off E-values: 10http://www.tcdb.org/and annotated autotransporter sequences were removed. The final dataset consisted of 6067 membrane protein sequences, and was scanned with AT47-HMM and AT47-bb-HMM. No  sequences were detected in this dataset.A validation for the twin-HMM search strategy was undertaken using the Transporter Classification Database (TCDB), which includes outer membrane proteins and trimeric-autotransporters and other transporters curated from genome data using annotations. TCDB was downloaded from i.e. had 100% sequence identity) between the AT47 and PF03797 models. These sequences were removed from the PF03797 set to result in a total of 196 sequences, which we used as the test data set. Application of the twin-HMM procedure to the test data set resulted in 168 hits when the AT47HMM model was applied, and 156 hits when the AT47HMM and AT47-bb-HMM model were applied sequentially. From this we can estimate the false negative rate as 20%. The rate of false positives was estimated by applying the twin-HMM procedure to the test data set consisting of 391 sequences collected from four PFAM models associated with protease activity . We chose protease activity because (a) some autotransporters are proteases, but (b) most proteases are not autotransporters. Application of the HMMs resulted in only two hits when the AT47HMM model was applied, and zero hits when AT47-HMM and AT47-bb-HMM models were applied sequentially. This suggested that the proposed twin-HMM procedure was a highly conservative method for the detection of autotransporters. More specifically, in the genomes analyzed we expect to detect 80% of autotransporters with the rate of false positives close to zero.In order to evaluate the rate of false negatives and false positives to be expected from searches using the twin-HMM search strategy, we made use of protein sequence datasets from PFAM. The PFAM protein family PF03797 (“autotransporter domain”) overlaps with, and is largely equivalent to, the barrel domain of autotransporters. A total of 212 sequences belonging to the PF03797 seed model were retrieved from the UniProt database. Our AT47 models (both AT47HMM and AT47-bb-HMM model) contained 47 sequences manually curated from the primary literature. Comparison with PF03797 showed that 16 sequences were shared (http://meme.sdsc.edu/) −5. These conserved regions were visualized on the 3D structures of BrkA (PDB: 3QQ2) http://www.pymol.org). Protein structures were downloaded from RCSB PDB (www.pdb.org) All calculations were carried out locally on a Linux system unless indicated otherwise. Conserved regions were investigated using MEME 4.5.0  of barrel-domain motifs sequences for 1523 putative autotransporters were generated using WEBLOGO (http://weblogo.berkeley.edu/) Analysis of the passenger domains (including the α-linker region) was undertaken by a similar means. Global sequence alignment was carried out on the training set passenger domains using EMBOSS-needle. Sequences showing similarity greater than 95% were removed and then motif analysis was carried out on the remaining 46 sequences. Conserved regions that were 5 to 300 residues long, present in all 46 passenger domains, and had a statistical significance  of 10http://www.clustal.org/) http://evolution.gs.washington.edu/phylip.html) http://itol.embl.de/) E. coli B088 (ZP_06661096.1). Six conserved regions detected in AT47 barrel-domain region, were scanned for in 1523 barrel-domain regions using HMMER. The passenger domain region was defined as downstream of predicted signal sequence and upstream of the barrel-domain in each of the 1523 sequences. Conserved domains were determined using Pfam-A families (http://pfam.janelia.org/) Klebsiella pneumoniae 342 (YP_002240364.1) serving as the outlier.Multiple sequence alignment of protein sequences was performed with ClustalW  The barrel-domain of BigE (shaded grey) shares 40% sequence identity (60% sequence similarity) to that of the protein from Ralstonia. A segment of unknown function from 220–528 (green) is repeated 8 times in BigE. BLAST searches revealed proteins related to the autotransporter from Ralstonia in five other species of Beta-Proteobacteria . The black box represents the N-terminal signal sequence of each protein. (B) Distinct regions of the passenger domain of BigE are highlighted: green-the series of domains noted above, yellow-internal repeats, grey-the barrel-domain. The internal repeat sequence highlighted in yellow is plotted as a Sequence Logo: it represents eight repeats of 69 amino acid residues. Hydrophobic residues are coloured black. Hydrophillic residues are coloured green, purple (amines) or red (acidic) according to their side-chain characteristics. The height of the letters indicates how well conserved a residue is in each position of the repeat. PsiPred secondary structure prediction suggests repeated β-strands (each indicated with an arrow) throughout this section of the BigE passenger domain.(PDF)Click here for additional data file.Figure S2Phylogenetic analysis of functional (passenger) domains. The active diagram contains all accession information for the 1523 autotransporter sequences. Sub-domain signatures were identified using Pfam analysis of all sequences, and these are represented as radiating coloured symbols. The length of this line is proportional to the number of residues in the passenger:α-linker domains.(PDF)Click here for additional data file.Figure S3Logos characteristic of the β-signal motif. In order to best represent the conserved features inherent in motif 5, a sequence Logo was constructed for the motif 5 sequences from each of the 13 (of 14) classes of barrel-domains shown in (PDF)Click here for additional data file.Table S1Forty-seven autotransporters dataset.(PDF)Click here for additional data file.Table S2Autotransporter detection in E. coli pathotypes.(PDF)Click here for additional data file.


B of Bacillus subtilis in response to energy limitation. RsbP has a predicted N-terminal Per-ARNT-Sim (PAS) domain, a central coiled-coil, and a C-terminal protein phosphatase M (PPM) domain. Previous studies support a model in which RsbQ provides an activity needed for PAS to regulate the phosphatase domain via the coiled-coil. RsbQ and the PAS domain (RsbP-PAS) therefore appear to form a sensory module. Here we test this hypothesis using bioinformatic and genetic analysis. We found 45 RsbQ and RsbP-PAS homologues encoded by adjacent genes in diverse bacteria, with PAS and a predicted coiled-coil fused to one of three output domains: PPM phosphatase (Gram positive bacteria), histidine protein kinase (Gram negative bacteria), and diguanylate cyclase (both lineages). Multiple alignment of the RsbP-PAS homologues suggested nine residues that distinguish the class. Alanine substitutions at four of these conferred a null phenotype in B. subtilis, indicating their functional importance. The F55A null substitution lay in the Fα helix of an RsbP-PAS model. F55A inhibited interaction of RsbP with RsbQ in yeast two-hybrid and pull-down assays but did not significantly affect interaction of RsbP with itself. We propose that RsbQ directly contacts the PAS domains of an RsbP oligomer to provide the activating signal, which is propagated to the phosphatase domains via the coiled-coil. A similar mechanism would allow the RsbQ-PAS module to convey a common input signal to structurally diverse output domains, controlling a variety of physiological responses.The RsbQ α/β hydrolase and RsbP serine phosphatase form a signaling pair required to activate the general stress factor σ Organisms monitor an array of external and internal signals to adjust their behavior to changing circumstances. Signal transduction proteins that sense and convey these cues are often of modular design, with distinct input (sensory) and output (effector) domains; signal-dependent modulation of the interactions between these domains controls information flow to downstream targets Bacillus subtilisB in response to energy limitation Understanding the means by which different PAS domains sense and communicate diverse signals is necessary to identify common themes. Here we use a bioinformatic and genetic approach to investigate a bacterial sensing module that consists of two parts: an α/β hydrolase and a separate PAS domain that is covalently attached to structurally diverse output domains in different organisms. As shown in rsbQP operon The structural genes for RsbQ and RsbP lie in the bicistronic B. subtilis. However, the predicted output domains covalently associated with these RsbP-PAS homologues included not only PPM phosphatases, but also histidine protein kinase and diguanylate cyclase domains. We report here the results of a PSI-BLAST search that found 45 such PAS-containing proteins, and a multiple alignment that suggested residues representative of the class. Genetic analysis indicated that some of these residues were essential for RsbP-PAS function in B. subtilis, and that one was important for direct interaction with RsbQ.During our initial BLAST searches to explore the distribution of domains related to RsbP-PAS, we noticed that its closest homologues were encoded in tandem with a clear RsbQ homologue, as is the case in B. subtilis rsbQP. Beginning with a query of RsbP residues 1-109 Alteromonas macleodii_B4RX87) from above the cut-off did have an RsbQ partner and was included to broaden sequence diversity. For convenience we refer to all 45 RsbP-PAS-like domains as RsbP-PAS.We used a PSI-BLAST Erythrobacter sp_A5P6T5). Other exceptions lacking the coiled-coil region include proteins in which one or two additional PAS domains lie C-terminal to RsbP-PAS; others that have an additional phosphodiesterase domain (EAL) C-terminal from a cyclase domain; and two that have no associated output domain, either because sequencing is incomplete (Oceanicola granulosus_Q2CB27) or possibly in error (Mesorhizobium sp_Q11AY1).We catalogued the domain architectures of the 45 proteins containing an RsbP-PAS homologue, based on profiles available in the Conserved Domain Database Streptomyces ambofaciens and S. pristiniaspiralis, both copies are associated with phosphatase output domains. In Psychromonas ingrahamii, both copies apparently regulate cyclic di-GMP metabolism. The PAS domain of one (A1SVT3) is linked to a diguanylate cyclase domain via a predicted coiled-coil, whereas that of the other (A1SX34) is linked to tandem cyclase and phosphodiesterase domains via a heterologous PAS domain. Based on the bioinformatic analysis, we conclude that RsbQ and RsbP-PAS form a bipartite input module that regulates the activity of at least three structurally different output domains.We note that three of the organisms included in We constructed a ClustalW alignment filter utility from the MPI Bioinformatics Toolkit To make the RsbP-PAS alignment, we used the HHet al. Comparison of the two multiple alignments indicated their close relationship. However, there were two striking differences. First, the outgroup sequences usually terminated with the widespread DIT motif identified by Möglich B. subtilis RsbP for further analysis: Q53, F55, C56, and Y59. Another nearby residue, P62, is highly conserved among RsbP-PAS homologues. However, in the absence of an experimentally determined structure, it is not clear whether this proline represents an unusual but key residue within Fα or acts instead as a helix-breaker. We therefore relied on the other four residues to represent Fα.These Fα differences are not altogether surprising because Eα, Fα and the FG loop represent the most diverse elements of the PAS fold B. subtilis RsbP. In total, nine representative residues were selected, and these were scattered throughout the predicted PAS structure in the A'A loop, Aβ, the EF loop, Fα, Gβ and Hβ.Further inspection suggested five additional residues for analysis . For exai-tasser server B. subtilis RsbP-PAS sequence against the four structures chosen by the server as the best templates  a cysteine, which binds heme in some molecular contexts. Notably, loss of the C56 side chain was not critical for function in our standard assay. By contrast, the side chains of L48, F55, Y59 and E72 were required, and side chain of P86 was an important contributor. We therefore focused on this second group of substitutions for the remainder of our study.The mild phenotypes conferred by the C10A and C56A single substitutions support two conclusions. First, cysteine residues are integral to well-characterized mechanisms of oxidative stress sensing Because PAS domains frequently modulate protein-protein interactions, we tested the five most deleterious substitutions for possible phenotypes in the yeast two-hybrid system. An earlier study found that RsbP appeared to interact with RsbQ in yeast Based on the plate lift assays summarized in The plate lift assays shown in B. subtilis cell extracts, but RsbP-F55A beads were unable to complex RsbQ under these conditions . This is contrary to the results of the yeast two-hybrid assay, and suggested that the intracellular environment might contain a factor important for the interaction. We developed a cell extract model to test this notion. Significantly, His-tagged wild type RsbP attached to Ni-NTA magnetic beads effectively pulled down native RsbQ from nditions . These rTo test the RsbP-RsbP interaction, we analyzed purified wild and mutant RsbP proteins on a Superose 12 size exclusion column . The wilThe behavior of the F55A substitution in yeast two-hybrid as well as pull-down assays indicated that the PAS domain was important for the interaction of full-length RsbP with RsbQ. Additional assays in the yeast two-hybrid system estimated the contribution of the different regions of RsbP to this interaction. Based on the data shown in B. subtilis RsbQP, the prototype signal transduction pathway employing this module, bears on the mechanism by which the RsbQ α/β hydrolase and the associated RsbP-PAS domain sense an activating signal.We used a bioinformatic analysis to identify a bipartite sensing module implicated in controlling three different output domains in diverse bacteria: PPM phosphatase, histidine protein kinase, and diguanylate cyclase. These output domains are commonly found in signal transduction pathways that control response to the local environment and thus contribute to bacterial adaptation and survival. Our genetic analysis of B. subtilis. This inference is based on the finding that the F55A substitution, which disrupted the RsbQ interaction in vitro, conferred a null signaling phenotype in vivo. These results can be understood in terms of two models in which direct contact between the α/β hydrolase and the PAS domain is required for signal transduction . In either case, we now suggest that the hydrolase must deliver this product to the hydrophobic cleft of the PAS fold by direct protein-protein interaction. In this model, the catalytic activity of the hydrolase is essential but PAS is the primary sensing domain.Model 1 is an extension of the earlier proposals of Brody g signal , left. Iright). The LuxPQ quorum sensing system of Vibrio harveyii provides one well-characterized example in which bacterial PAS domains serve as sites of interaction with a separate sensing protein By contrast, in Model 2 the α/β hydrolase is the sensor. Here the activating molecule binds within the catalytic site of the hydrolase, and this occupancy is signaled to the PAS domain by direct contact , right. How might the RsbQ α/β hydrolase interact with RsbP-PAS? Intra- and intermolecular interactions of PAS domains are commonly mediated by the five-stranded anti-parallel β sheet, which is the most highly conserved region of the domain, and may also involve pathway-specific N- or C-terminal helices that flank the β2-α4-β3 core structure et al. How might RsbP-PAS communicate with structurally diverse output domains? Möglich B. subtilis RsbP are consistent with the general model of PAS interdomain signaling of Möglich et al. et al. pcoil program, and in accord with the general model The results of our study of B. subtilis is the regulatory target of the module known. Because the RsbP phosphatase is normally required for activation of the general stress factor σB in response to energy depletion B. subtilis network via the RsbW kinase, whose Km for ATP is in the physiological range B activity by countering the activity of the RsbW kinase  a decrease in ATP levels B signaling network of Listeria monocytogenes is also activated by red light B activity in the related B. subtilis and L. monocytogenes, or the RsbQ-PAS module senses a parameter other than red light.Two studies have shown that the RsbP phosphatase is required for the energy branch of the σIdentification of the substrate for the RsbQ hydrolase would provide an important clue to the signal sensed by the RsbQ-PAS module. Among the bacteria shown in Bacillus subtilis strains shown in B. subtilis were as described by Brody et al. All constructed rsbP was done using the integrative plasmid pNE5959 as a template. pNE5959 carried 445 bp from the 3′ portion of the rsbQ coding sequence, the entire rsbP coding sequence, and an additional 110 bp downstream from the rsbP termination codon. It was generated by amplifying a 1.8 kb fragment from B. subtilis genomic DNA with primers QP_EcoRI (GAATTCCTTGCTATTTGAATGATCCG-3′5′-TACCG) and P_EcoRI_Rev_full (GAATTCCTTCCTTGCAGGTGTTTCA-3′5′- TACCG), both containing EcoRI sites (underlined). The resulting fragment was cloned into EcoRI-cut pUS19 to yield pNE5959. Point mutations were made in the rsbP coding sequence using the QuikChange Lightning kit according to the manufacturer's protocol , creating alanine substitutions at C10, L13, L48, Q53, F55, C56, Y59, E72, and P86. The expected alteration and the integrity of the rsbP coding sequence in each construct were confirmed by DNA sequencing.Site-directed mutagenesis of rsbPΔ2 amyE::ctc-lacZ). In addition to the rsbPΔ2 in-frame deletion, which removed triplets 31–117 from the rsbP coding sequence, PB715 also contains a σB-dependent ctc-lacZ reporter fusion in single copy at the amyE locus. The resulting transformants were merodiploids with only one copy of rsbP expressed from the rsbQP promoter. Transformants with the active copy containing the RsbP substitutions (and the inactive copy containing the rsbPΔ2 deletion) were identified by PCR screen.These substitution constructs were transformed into strain PB715 .Bacterial shake cultures were grown at 37°C in Buffered Luria Broth medium lacking salt  before onset of stationary phase and broken by sonication. Total cell protein was separated by SDS-PAGE, transferred to polyvinylidene difluoride membranes (Bio-Rad Laboratories), and probed with rabbit anti-RsbP antibody, as previously described rsbQ and rsbP reading frames were previously fused to either the GAL4 DNA binding domain in plasmid pGBT9 or the GAL4 activation domain in plasmid pGAD424 rsbP reading frames encoding PAS null substitutions L48A, F55A, Y59A, E72A, and P86A. We also made constructs expressing fusions to different regions of rsbP: PAS alone (residues 1-111); predicted coiled-coil and PPM phosphatase (110–403); or PPM alone (167–403). Integrity of the fusion junctions and coding regions was confirmed by sequencing. Constructs were then paired in yeast SFY526 cells by selecting double transformants on minimal plates. Transcriptional activation of the lacZ reporter gene in the resulting transformants was determined qualitatively using a colony lift filter assay, or quantitatively by performing β-galactosidase assays on cultures grown in liquid media, according to the manufacturer's protocol. Activities of the RsbP, RsbP-F55A, or RsbP-P86A constructs in the GAL4 DNA binding domain alone (self-activation) were subtracted from the pairwise activities shown in We used the Matchmaker Two-Hybrid System  to compare interactions between RsbQ and wild or mutant versions of RsbP. Full-length E. coli BL21 (DE3). Expression was induced by IPTG and proteins purified under native conditions on nickel affinity columns , essentially according to the manufacturer's protocol. Following the standard wash with buffer NPI-20 , we employed two initial step gradients of NPI-50 and NPI-100 . RsbP or RsbP-F55A was then eluted with NPI-250 (containing 250 mM imidazole). Concentrations were determined with the Protein Assay Reagent, and purity was assessed by SDS-PAGE.Plasmids encoding His-tagged wild or the F55A mutant form of RsbP in the Novagen pET15b vector  were transformed into 2PO4, pH 8, 50 mM NaCl, 20 mM imidazole). The RsbP-coated beads were added to clarified extract from sonicated, stationary-phase B. subtilis cells (300 µg protein in 100 µl Buffer A); this mixture was incubated for 1 hour at 37°C on a roller drum. The supernatant was removed, the beads were washed three times with 100 µl aliquots of Buffer A, and RsbP was eluted with Buffer B . Supernatant (unbound) and elution (bound) fractions were separated by SDS-PAGE; Western blots were probed with anti-RsbQ antibody E. coli proteins from the same affinity column fraction in which RsbP would normally elute, but isolated from BL21 (DE3) cells containing an empty pET15b vector; and (ii) untreated beads alone.For pull-down assays, fractions containing His-tagged wild or mutant RsbP were desalted using Zeba Desalt Spin Columns  and stored in 20 mM Tris-HCl, pH 6.9. 1 µg wild or mutant RsbP was bound to 10 µl of Ni-NTA magnetic agarose beads (Qiagen) in a total volume of 25 µl Buffer A  using Amicon Centricon-30 filters , then applied to a Superose 12 column , equilibrated at 4°C with the same buffer. Proteins were eluted at a flow rate of 0.25 ml/min, using a Bio-Rad automated fast protein liquid chromatography system. Column calibration was done with a kit of standard proteins .rsbQ homologue, based on the Reference Sequence Database rsbQ homologue; these PAS sequences formed the core of the dataset for further analysis. One additional sequence not clustered with the first 44 was found manually (Alteromonas macleodii). It was added to the dataset for a total of 45 RsbP-PAS-like sequences.Analysis of bacterial genomes for the presence of RsbP-PAS homologues was done using the PSI-BLAST algorithm lignX from the Vector NTI 9.0.0 software package , using the BLOSUM62 scoring matrix and default program settings; the dendogram shown in pcoil program run with the MTIDK matrix and a weighting for non-polar residues at appropriate positions, using a scanning window of 21 residues Multiple alignment of the 45-member dataset was done with AlustalW filter utility from the MPI Bioinformatics Toolkit http://toolkit.tuebingen.mpg.de/hhfilter). The alignment of the 24 representative RsbP-PAS-like sequences shown in lustalW color code for amino acid residues, as described in the figure legend. For comparison we performed a similar multiple alignment of a set of outgroup sequences that are closely related to RsbP-PAS but lack an RsbQ partner. From the same PSI-BLAST search that provided the 45 RsbP-PAS-like sequences shown in filter; these were aligned against the previous profile of the 24 RsbP-PAS-like sequences using ClustalW  and represent the relative conservation of the predicted Fα helices of RsbP-PAS-like and outgroup sequences. Tertiary structure of the RsbP PAS domain shown in i-tasser server (http://zhanglab.ccmb.med.umich.edu/I-TASSER/); this model had a favorable confidence score of 0.80, suggesting an RMSD of 2.6 (+/- 1.9) Å, relative to the true structure Sinorhizobium meliloti FixL (PDB ID: 1EW0_A), B. subtilis YtvA (PDB ID: 2PR5), E. coli DosH (PDB ID: 1S66_L), and Azotobacter vinelandii NifL (PDB ID: 2GJ3_A). These templates all have bound heme or flavin cofactors. However, thus far no cofactor has been found associated with B. subtilis RsbP .Logos shown in Figure S1Multiple alignment of PAS homologues from the comparison outgroup. 24 representative sequences related to RsbP-PAS but missing a clear RsbQ partner were aligned to the ClustalW profile of RsbP-PAS-like domains that have an RsbQ partner (B. subtilis RsbP ( partner . Sequenclis RsbP . The plolis RsbP .(TIF)Click here for additional data file.Figure S2Multiple alignment of RsbQ homologues. ClustalW alignment of the 24 RsbQ homologues encoded immediately adjacent to the RsbP-PAS-like domains shown in et al. B. subtilis RsbQ (Bsu_O07015), and these residues are highly conserved. The same analysis suggested additional residues that could affect RsbQ function, indicated by the black circles above F27, V97, F136 and F196, and these too are highly conserved. F27 and V97 were proposed to interact with substrate in the hydrophobic cavity that contains the catalytic triad; F136 and particularly F196 were proposed to impede substrate access to the same cavity. This cavity and a unique loop adjacent to F136 distinguish RsbQ from similar haloperoxidases. The position of this loop is shown by a black line above L126-G135; loop length is variable but its N- and C-terminal regions are conserved. Kaneko et al. (TIF)Click here for additional data file.


Drosophila melanogaster RPTPs as a model system. Biochemical studies reveal contrasting roles for the D2 domain of Drosophila Leukocyte antigen Related (DLAR) and Protein Tyrosine Phosphatase on Drosophila chromosome band 99A (PTP99A). While D2 lowers the catalytic activity of the D1 domain in DLAR, the D2 domain of PTP99A leads to an increase in the catalytic activity of its D1 domain. Substrate specificity, on the other hand, is cumulative, whereby the individual specificities of the D1 and D2 domains contribute to the substrate specificity of these two-domain enzymes. Molecular dynamics simulations on structural models of DLAR and PTP99A reveal a conformational rationale for the experimental observations. These studies reveal that concerted structural changes mediate inter-domain communication resulting in either inhibitory or activating effects of the membrane distal PTP domain on the catalytic activity of the membrane proximal PTP domain.Signaling mechanisms involving protein tyrosine phosphatases govern several cellular and developmental processes. These enzymes are regulated by several mechanisms which include variation in the catalytic turnover rate based on redox stimuli, subcellular localization or protein-protein interactions. In the case of Receptor Protein Tyrosine Phosphatases (RPTPs) containing two PTP domains, phosphatase activity is localized in their membrane-proximal (D1) domains, while the membrane-distal (D2) domain is believed to play a modulatory role. Here we report our analysis of the influence of the D2 domain on the catalytic activity and substrate specificity of the D1 domain using two  Drosophila melanogaster, five Receptor Protein Tyrosine Phosphatases (RPTPs) control the growth of retinal axons and influence their ability to contact specific zones and prevent midline crossing of longitudinal axons Drosophila embryo The activity of Protein Tyrosine Phosphatases (PTPs) is critical for the regulation of signaling networks that govern cell growth, differentiation and communication. Changes or defects in the activities of either tyrosine phosphatases or kinases substantially perturb signaling pathways resulting in different diseased pathologies DLAR (Drosophila Leukocyte-Antigen-Related-like) and PTP99A (Protein Tyrosine Phosphatase on Chromosome band 99A7-8) play a key role in intersegmental nerve (ISN) branch-point decisions. While the guidance decision of the ISN axons to navigate past their first branch point requires concerted activity of DLAR and PTP99A, the entry of the Segmental Nerve b (SNb) into the Ventrolateral Muscle field depends on the tightly modulated antagonistic actions of the two RPTPs in vivo activity and substrate preferences could be altered for human LAR when its D2 domain was exchanged with that of CD45 A prominent feature of a PTP domain is the conserved active site cysteine that serves as a nucleophile to attack the phosphate of the phosphotyrosine residue. Also, a conserved aspartate residue acts as a general acid to provide its proton to the leaving group, resulting in the formation of a cystienyl-phosphate enzyme intermediate . This aspartate residue then acts as a general base and along with two conserved glutamine residues activates a water molecule to dislodge this intermediate releasing the inorganic phosphate NheI and XhoI restriction sites of the bacterial expression vectors pET-15b and pET-22b. The active site mutants (with the nucleophilic cysteines in the PTP domains of DLAR and PTP99A mutated to serines) were obtained by using a single primer approach. An XbaI site was incorporated in the primers to aid screening of mutants. All clones were confirmed by sequencing (Macrogen Inc.). The details of the expression constructs are compiled in Cosmids containing the genes encoding RPTPs DLAR and PTP99A were a kind gift from Prof. Kai Zinn . The PTP domains of PTP99A and DLAR were PCR amplified and ligated between the E. coli BL21(DE3) cells . Cells were grown to an optical density of 0.6 at 37°C in Luria Broth and induced with 0.1 mM IPTG. Following induction, the temperature for growth was lowered to 12°C and cells were grown for an additional 10–12 hrs before they were spun down and stored at −80°C. For purification of the recombinant PTP domains, cells were lysed by sonication in a buffer containing 50 mM Tris-HCl pH 8.0, 250 mM NaCl, 5% Glycerol and 1 mM β-mercaptoethanol (βME). The supernatant was incubated with His-Select Ni-NTA affinity resin (Sigma-Aldrich Inc.). After a wash with lysis buffer containing 20 mM Imidazole, the protein was eluted in 50 mM Tris-HCl pH 8.0, 250 mM NaCl, 1 mM βME and 200 mM Imidazole. The eluted protein was dialyzed overnight against 50 mM Tris-HCl pH 8.0, 50 mM NaCl and 1 mM βME. This was then loaded onto a Q-sepharose  anion exchange column that had been pre-equilibrated with 20 mM Tris–HCl pH 8.0 and 1 mM βME. After extensive washing with Tris-HCl, the protein was eluted from the column by gradient of 0–1 M NaCl. Purity of the samples was assessed by SDS – PAGE. Concentrations of the proteins were accessed by their absorbance at 280 nm using their molar extinction coefficients.The plasmids containing the recombinant PTP domains were transformed into Substrates of PTPs characterized thus far include the activation loop segments of various kinases and regulatory loops of other signaling proteins. Suitably designed peptide substrates mimic the physiologically relevant substrates of PTPs para-Nitrophenylphosphate (pNPP), a small molecule generic substrate, as well as phosphotyrosine containing peptides. The pNPP assay was performed as reported previously Phosphatase activity of the recombinant PTP domains was determined by using 5.0 µM of recombinant protein was titrated with increasing concentrations of PNC (Sigma-Aldrich) in 25 mM citrate buffer pH 6.5, 100 mM NaCl and 2 mM DTT. The closing of the WPD loop leads to the quenching of the intrinsic tryptophan fluorescence The binding of phosphotyrosine peptides to the PTP domains was studied by Surface Plasmon Resonance on a Biacore-2000 instrument  The sequences of the full length DLAR and PTP99A RPTPs were obtained from the Flybase database (FBgn0000464 and FBgn0004369 respectively). The different domains in the sequence were identified using the conserved domain database at the NCBI + or Cl− ions. The first derivative method of steepest descent in energy minimization was used to attain a potential energy minimum for the system before subjecting the same to MD simulations. Following isothermal-isochoric (NVT) and isothermal-isobaric (NPT) equilibration, the system was subjected to kinetic perturbations under the OPLS-AA/L all-atom force field of the GROMACS program at 300 K for 20 nanoseconds each. The Root Mean Square Deviation (RMSD) of the simulated structures from the initial structural model showed the system stabilizes by ca 7 nsec. All the structures were analyzed with snapshots taken between 10 nsec–20 nsec trajectory time. The Xmgrace software was used for numerical graphs and interpretation of data. Previously well studied closed and open forms of PTP1B (PDB IDs 1SUG and 2HNQ respectively) were used for the MD simulations primarily as a control model to evaluate the success of the simulations Homology models of various proteins have been used to study their conformational features by molecular dynamics E. coli and were purified using the protocols described earlier  and DLAR (DLAR D1D2) , the individual PTP domains (D1 and D2) as well as the active site mutants were expressed in  earlier , b & c [2 domain . Mutatio2 domain .The ability of the PTP domains of DLAR and PTP99A to dephosphorylate peptide substrates was used to evaluate the substrate recognition features of the two enzymes. DLAR and PTP99A were found to have distinct catalytic efficiencies for different peptide substrates . In the cat/Km of the D1D2 PTP constructs with that of the D1 domains of DLAR and PTP99A to obtain ratios of their catalytic efficiencies revealed inherent differences in the sequence specificity of their D2 domains (4 sec−1 M−1 between Cuticle and Myospheroid peptides) when compared to DLAR D1 alone (∼130.0×104 sec−1 M−1 between Insulin Receptor and Abelson peptides). This suggests that the DLAR D2 domain plays a role in sequestering peptide substrates. The difference between the most and least preferred substrate in the case of PTP99A D1D2 was however much more (∼152.0×104 sec−1 M−1 between Insulin Receptor and Nervous Fingers peptides) when compared to its D1 domain (∼30.0×102 sec−1 M−1 between Abelson peptide and Insulin Receptor peptides) suggesting an activating role for its D2 domain. A more comprehensive study of this activation mechanism is being reported elsewhere.A comparison of the k domains . The pepD values for the first binding site for the DLAR D1HSS D2 construct (87.5 µM for the Cuticle peptide and 1.65 µM for the Insulin Receptor peptide) suggests that D1 is inherently more suited to bind the Insulin Receptor peptide. The D2 domain, in the absence of D1, does not bind the Insulin receptor peptide with the same affinity. We note that non-phosphorylated peptides did not interact with the immobilized proteins. This observation is consistent with the hypothesis that the phosphotyrosine residue is essential for PTP-substrate interaction.Surface Plasmon Resonance (SPR) experiments performed to evaluate the binding of peptide substrates to DLAR highlighted the role of the active site cystiene in peptide binding to the PTP domain. Another feature that was evident from the sensograms is that both Insulin Receptor peptide and the Cuticle peptide interactions for DLAR D1D2, DLAR D1HSS D2  was used. PNC acts as a small molecule competitive inhibitor of the PTPs as it mimics the phosphotyrosine residue To evaluate the differences in the phosphotyrosine binding pockets of the two domains of DLAR and PTP99A, a small molecule probe 2 and 2036 Å2 of buried surface area between the two domains of DLAR and PTP99A respectively).Molecular dynamics simulations on PTP99A and DLAR provided vital insights into the interactions between the tandem PTP domains in double domain PTPs. The distance between the centroids of the two domains mapped over simulation time did not change much for both DLAR and PTP99A. The average distance between the centroids of the two domains of DLAR and PTP99A was 3.74±0.02 nm and 3.83±0.04 nm respectively . The twoα atom as well as for each atom per residue over the MD simulation time  were represented as N×N colour coded matrices (N = number of residues in the protein). All the six PTP domains examined showed a similar matrix which could be interpreted as a signature of the PTP fold. This inter-atomic interaction map has a shape like a butterfly where the body and wing comprise of interactions concentrated around the motifs 2, 3, 4, 5, 6 and 7 which form the core of the PTP domain . The heaDrosophila PTP domains. While the active site of the DLAR D1 domain was tightly packed with a substantial number of non-covalent interactions with neighboring residues, the corresponding cluster in the D1 domain of PTP99A had fewer interactions. Also, in the D1 domain of DLAR, one of the glutamines of the Q loop was seen to interact with the R loop, while this interaction was absent in the D1 domain of PTP99A. Trp of the WPD loop of the D1 domain had more interacting partners and clustered differently when compared to the corresponding Trp residue of the D2 domain. These interaction networks thus reveal differences in the substrate binding and the active site hubs in the PTP domains of DLAR and PTP99A.The inter-atomic matrix provided a basis for an analysis of the interaction network between the 20 functionally important residues (FIRs) of the PTP domain . The FIRhttp://caps.ncbs.res.in/download/dlar_ptp99a/). Importantly, both glutamines of the Q loop of the D1 domain of DLAR were seen to cluster with the R loop when the D1 domain was present in isolation. This interaction was uncoupled in the presence of the D2 domain of DLAR where one of the glutamines now clustered separately. This could perhaps account for the decrease in the activity of the D1 domain of DLAR in the presence of its D2 domain as it disrupts the glutamine network with the active site residues. Interestingly, in the case of PTP99A, the residues of the WPD loop formed a separate cluster from the active site when the D1 domain was present alone. This WPD loop cluster was seen to be merged with the active site residues in the presence of the D2 domain. It thus appears likely that the D2 domain of PTP99A enhances the activity of its D1 domain by strengthening the interaction networks between the active site residues and the WPD loop.Molecular Dynamics simulations performed on the D1 domain alone of both DLAR and PTP99A revealed the effects of the presence of D2 on the interaction networks more explicitly  and S4. Drosophila oogenesis suggesting that these domains are used in distinct signaling pathways and cell fate decisions in Drosophila development Differences in the functional roles of RPTPs have often been explained by sequence-structure variations as well as spatio-temporal effects in developmental processes. The role of extracellular domains of these RPTPs is clear from unambiguous genetic data - deletions in the Immunoglobulin–like domains of DLAR are lethal, while deletions in the Fibronectin type III repeats are not. The Fibronectin type III repeats are essential for The tandem PTP domains of double domain RPTPs form an interesting model system. In particular, the role of the catalytic D2 domain in the function of these proteins is unclear from genetic data. For example, the D1 domains of DLAR and DPTP69D have been examined for their ability to rescue the homozygous deletion mutations of these genes. In the case of DLAR, D1 was found to be redundant as D2 could itself partially rescue the DLAR −/− phenotype pNPP and the phosphotyrosine peptide substrates, reveal that the D2 domain of DLAR has an inhibitory effect on its D1 domain while the D2 domain of PTP99A enhances the activity of its D1 domain. Substrate recognition features were also substantially influenced by the presence of the D2 domain in both cases. In the DLAR D1D2 construct, when the most preferred substrate of the D1 domain (the Insulin Receptor peptide) is sequestered by the D2 domain, the Cuticle peptide is preferentially de-phosphorylated. This perhaps explains the observation that D2 deletion constructs are significantly impaired in phenotypic rescue of the embryos Drosophila embryos A combination of biochemical studies using activity measurements, protein-substrate interactions and MD simulations were performed to understand the molecular basis of modulation of phosphatase activity in the two tandem PTP domains of DLAR and PTP99A. These studies reveal that the entire phosphatase activity in the two proteins is localized to their D1 domains. The presence of the D2 domains, however, leads to a change in their catalytic activity. Phosphatase activity, monitored using both The D2 domain of PTP99A, while structurally conserved, has critical mutations in motifs 9 and 10 suggesting a loss of catalytic activity . The actMD simulations of the PTP domain models were used to understand the conformational basis of the interaction between the two PTP domains of DLAR and PTP99A. As the linker connecting the two PTP domains is crucial for maintaining the substrate specificity of the LAR and LCA RPTPs To evaluate the role of other conserved protein segments in inter-domain interactions, the inter-atomic network of the PTP domains were examined for each residue (within 5 Å) for each PTP domain. While the butterfly pattern of the PTP fold was observed in all the four PTP domains, alterations in the networks of functionally important residues (FIRs) could rationalize the differences in the biochemical properties of the PTP domains. We speculate that the smaller clusters in the D1 domain of PTP99A compared to that of DLAR could be correlated with the low intrinsic activity of the PTP99A protein. Differences in the network between the active site Arg, the general acid Asp, the Trp at the hinge and the peptide recognition residues between the D1 domains of DLAR and PTP99A reflect the differences in their substrate recognition features. Substitution of two critical amino acids, leading to the loss of activity in the D2 domains of the LAR family (Motif 1 Tyr and the Motif 8 Glu) A comparison of PTP sequences to understand the evolution of PTP domains suggests that the inactive D2 domains evolved from a common ancestor. The ancestor then appears to have delineated to form two subsets: one subset which accumulated mutations around the active site, and the other which accumulated mutations at its backside Figure S1Purification profile of the recombinant PTP proteins used in the present study. A: Schematic to show the different mutants used in the present study. B and C: Purified constructs of the catalytic domains of DLAR. Lane 1: DLAR D1D2, Lane 2: DLAR D1HSS D2, Lane 3: DLAR D1 D2HSS Lane 4: DLAR D1HSS D2HSS, Lane 5: DLAR D2, Lane 6: DLAR D2HSS, Lane 7: DLAR D1, Lane 8: DLAR D1 HSS, Lane 9: PTP99A D2, Lane 10: PTP99A D1, Lane 11: PTP99A D1D2, Lane 12: PTP99A D1 HSS, Lane 13: PTP99A D2, Lane 14: PTP99A D1HSS D2, M: Molecular weight marker.(TIF)Click here for additional data file.Figure S2Surface electrostatic potential distribution in DLAR and PTP99A. The electrostatic potential at the surface of DLAR and PTP99A as estimated by the APBS tool (Pymol software). The phospho-tyrosine binding pocket of each domain of DLAR and PTP99A is highlighted. Active site residues in the binding site are represented as sticks.(TIF)Click here for additional data file.Figure S3Interaction networks for the 20 Functionally Important Residues (FIR) of the D1 domain of DLAR. The interaction network for the FIRs were computed over 2 ns time scales for the D1 domain of DLAR in the presence and absence of its cognate D2 domain.(TIF)Click here for additional data file.Figure S4Interaction networks for the 20 Functionally Important Residues (FIR) of the D1 domain of PTP99A. The interaction network for the FIRs were computed over 2 ns time scales for the D1 domain of PTP99A in the presence and absence of its cognate D2 domain(TIF)Click here for additional data file.Figure S5Characterization of the D958C mutant of the D2 domain of PTP99A. A: Size exclusion profile of wild-type and D958C mutant of the D2 domain of PTP99A. B: Circular Dichroism (CD) spectra of the wild type and D958C mutant. The D958C mutation does not alter the secondary structure of the D2 domain. C: para-Nitrophenyl Phosphate assay for the phosphatase activity for different constructs of PTP99A. The D958C point mutant is catalytically inactive.(TIF)Click here for additional data file.Table S1List of primers used for the cloning of the recombinant PTP domains of DLAR and PTP99A(DOC)Click here for additional data file.Table S2Kinetic parameters obtained for the dephosphorylation of various substrates by the active constructs of DLAR and PTP99A.(DOC)Click here for additional data file.Table S3Sequence motifs defining the PTP domain of DLAR and PTP99A.(DOC)Click here for additional data file.Table S4RMSF for the ten sequence motifs defining the PTP domains of DLAR and PTP99A.(DOC)Click here for additional data file.Table S5Residue numbers for the functionally important residues (FIR) as they occur in the sequence of DLAR and PTP99A, and as they are seen in the homology models of the RPTPs used in the Molecular Dynamics Simulations.(DOC)Click here for additional data file.


The currently known protein sequence space consists of millions of sequences in public databases and is rapidly expanding. Assigning sequences to families leads to a better understanding of protein function and the nature of the protein universe. However, a large portion of the current protein space remains unassigned and is referred to as its “dark matter”.Here we suggest that true size of “dark matter” is much larger than stated by current definitions. We propose an approach to reducing the size of “dark matter” by identifying and subtracting regions in protein sequences that are not likely to contain any domain.Recent improvements in computational domain modeling result in a decrease, albeit slowly, in the relative size of “dark matter”; however, its absolute size increases substantially with the growth of sequence data. The protein universe is the collection of all proteins of every biological species that lives or has lived on earth. Its basProteins are composed of one or more domains, parts that are conserved in sequence and structure and that can evolve and function independently. SeveralThe use of profile hidden Markov models (HMMs) that capture the conserved sequence features of protein domains,13,14 isIn this study, we propose to expand the definition of “dark matter” by including regions in partly covered protein sequences that are not characterized and do not have any domain match. In addition to domain coverage, detecting regions in protein sequences that are unlikely to contain any domain considerably reduces the size of “dark matter”. Finally, we show that despite substantial improvements in computational domain modeling and tools for their identification, the relative size of “dark matter” decreases slowly, while its absolute size increases dramatically with the growth of sequence data.Currently defined “dark matter” of the protein sequence universe includes protein sequences that cannot be matched to any known protein family. This deMany resources for computational domain finding exist. The original “dark matter” analysis by Levitt utilized CDD profiles. HoweverEscherichia coli[E. coli enterobacterial species, a fact that has been also well established in the literature[de facto it remains a part of “dark matter”.This point can be further illustrated by the following example. Figurechia coli. Fifty pterature. The covBased on arguments presented above, we determined that Pfam domain models are better suited for the purpose of defining the size of “dark matter” in the protein sequence space. Furthermore, the data on Pfam coverage of a large sequence space is available for comparison. The latest Pfam release (Pfam 26) is reported to cover nearly 80% of protein sequences in the UniProtKB database, but only 57% of amino acid (aa) residues in all protein sequences in this database. We ran Parts of protein sequences that do not contain domains often contain smaller functional elements, such as transmembrane helices and signal peptides. Low comAs we have shown above, various computationally identifiable regions in protein sequences  cannot be used to reduce the size of “dark matter”. However, a large section of “dark matter” apparently can be effectively predicted not to contain any domain. Once all domains are identified in all protein sequences, we can identify regions that are both (i) too short to contain a domain and (ii) are located in positions between pairs of known domains or between a known domain and the protein terminus (N or C). For example, such positions are shown in grey on Figure 1. To calculate the contribution of such regions to the total sequence space, we decided to set their size limit at 50 aa. The reason behind this number is that whereas some domains are smaller than 50 aa, domains are never located adjacent to each other without at a least a small connecting linker. The average size of interdomain linkers was calculated to be 6-8 aa. Thus, aTo find out how progress in sequencing and improvements in domain models change computational coverage of protein space, we have reconstructed past events by applying domain coverage by three consecutive Pfam releases: Pfam 22, Pfam 24The trend shown on FigureComputational coverage of the protein sequence space, which is generated by genome sequencing projects, is an important process for our understanding of life. We propose a biologist-centered view on current computational coverage, where not only completely non-covered protein sequences, but also parts of partially covered protein sequences that are not occupied by protein domains are considered “dark matter”. Using high-throughput computing we show that the unexplored space of the protein sequence universe is larger than previously defined and that despite substantial improvements in bioinformatics during the last three years, the relative size of “dark matter” is decreasing very slowly.The following releases of the NCBI nr (non-redundant) database were used: April 4, 2009 (nrApr09), September 9, 2010 (nrSep10), and December 8, 2011 (nrDec11). The UniProtKB release September 2012 was used to calculate its domain coverage. Domain models/HMMs were retrieved from the three recent versions of the Pfam protein families database (Pfam-A portion only): Pfam 22.0 Pfam 24.hmmscan of the HMMER v.3.0 package[hmmpfam of HMMER v.2.3.2 adapted for the Kraken supercomputer, as described earlier[Protein sequence regions were identified using standard software packages and cutoffs: low-complexity regions, SEG; coiled  package with the package with def earlier. The amiAll computational analyses were performed in a local computing environment. Computationally intensive tasks were carried out using the Intel X86_64 Linux cluster (Newton) with a total of 4,200 processor cores at the University of Tennessee and the Cray XT5 supercomputer (Kraken) with a total of 112,896 processor cores at the Oak Ridge National Laboratory. Tasks were automated using a combination of C, PHP, and MPI scripts.The author(s) declare that they have no competing interestsBR, GDP and IBZ conceived the study and designed the research. BR and GDP carried out software design and computational analysis. BR, KW and IBZ analyzed the results and wrote the paper. All authors read and approved the final manuscript.


Phosphodiesterases (PDEs) are critically involved in the determination of intracellular cyclic nucleotide levels. PDEs are heterodimers containing a conserved C-terminal catalytic domain and an N-terminal regulatory domain. Within their regulatory domain, 5 PDE families contain GAF domains, which are potential cyclic nucleotide binding domains. cGMP is known to activate PDEs 2 and 5.Also PDE10 and 11 contain GAF domains in their N termini. However, the functional role of these domains remains a matter of debate. In chimeric constructs of PDE GAF domains and cyanobacterial adenylyl cyclase catalytic domains, cAMP and cGMP activated constructs containing the PDE10 and PDE11 GAF domains, respectively. On the other hand, binding of cAMP and cGMP was claimed not to activate the PDE10 and PDE11 holoenzymes.Here we used synthetic ligands identified by fluorescence resonance energy transfer (FRET)-based analysis of isolated GAF domains to demonstrate that PDE10 and 11 holoenzymes are activated by their GAF domains. Furthermore, we show that PDE10 is activated by cAMP and that PDE11 albeit sensitive to synthetic GAF ligands is not activated by the physiological nucleotides cGMP and cAMP.