Protein domains represent the basic units in the evolution of proteins. Domain duplication and shuffling by recombination and fusion, followed by divergence are the most common mechanisms in this process. Such domain fusion and recombination events are predicted to occur only once for a given multidomain architecture. However, other scenarios may be relevant in the evolution of specific proteins, such as convergent evolution of multidomain architectures. With this in mind, we study glutaredoxin (GRX) domains, because these domains of approximately one hundred amino acids are widespread in archaea, bacteria and eukaryotes and participate in fusion proteins. GRXs are responsible for the reduction of protein disulfides or glutathione-protein mixed disulfides and are involved in cellular redox regulation, although their specific roles and targets are often unclear.In this work we analyze the distribution and evolution of GRX proteins in archaea, bacteria and eukaryotes. We study over one thousand GRX proteins, each containing at least one GRX domain, from hundreds of different organisms and trace the origin and evolution of the GRX domain within the tree of life.Our results suggest that single domain GRX proteins of the CGFS and CPYC classes have, each, evolved through duplication and divergence from one initial gene that was present in the last common ancestor of all organisms. Remarkably, we identify a case of convergent evolution in domain architecture that involves the GRX domain. Two independent recombination events of a TRX domain to a GRX domain are likely to have occurred, which is an exception to the dominant mechanism of domain architecture evolution. Domain duplication and shuffling by recombination and fusion, followed by divergence are the more frequent mechanisms for the evolution of proteins . It has β-sheet flanked by several α-helices on either side of the β-sheet [Saccharomyces cerevisiae of three GRXs  with CSYS, CPYS and CPDC active site motifs [A protein domain of small size that is known to participate in the architecture of multidomain proteins and is widespread over the many branches of the evolutionary tree would be an appropriate choice to study. The glutaredoxin (GRX) domain meets all these conditions. It has approximately one hundred amino acids, it is a part of several multidomain architectures and it is present in archaea, bacteria and eukaryotes. GRXs are thiol oxidoreductases responsible for the reduction of protein disulfides or glutathione-protein mixed disulfides, which employ reduced glutathione (GSH) as hydrogen donor . Togethe β-sheet . Functio β-sheet . Alterna β-sheet . Three G β-sheet . Finally β-sheet ,13. Thise motifs -16.S. cerevisiae Grx3 and Grx4 [Multidomain proteins that contain GRX domains have also been reported in a variety of different organisms ,13,17-19and Grx4  and humaand Grx4  are examS. cerevisiae [Most GRXs are likely to participate in a diversity of processes that require redox-type regulation, although their specific roles and targets in those processes are often unclear. Examples of processes in which CPYC class GRXs are involved in include activation of ribonucleotide reductase, or 3'-phosphoadenylylsulfate reductase, reduction of ascorbate, regulation of the DNA binding activity of nuclear factors, or protection against heavy metals (reviewed in ). Examplrevisiae ,18,22, crevisiae ,24, PROKrevisiae , and regrevisiae .et al. [In this work we analyze the distribution and evolution of GRX domains in archaea, bacteria and eukaryotes. We study over one thousand proteins, containing at least one GRX domain, from hundreds of different organisms and trace the origin and evolution of the GRX domain within the tree of life. Our phylogenetic analysis suggests that single domain GRX proteins of the CGFS class have evolved through duplication and divergence from one initial gene that was present in the last common ancestor (LCA) of all organisms. The same appears to hold true for single domain GRX proteins of the CPYC class. We predict sets of residues that are likely to be important for protein function in the CGFS and CPYC classes of GRXs. Remarkably, we identify a case of convergent evolution in domain architecture, where two independent recombination events of a TRX domain to a GRX domain are likely to have occurred. We also identify domain combinations that, in the context of GRX domain evolution, appear to function as the supra-domains proposed by Vogel et al. .We have made a systematic identification of GRX domains from the UNIPROT database (information summarized in Table Embriophita) and in single domain proteins. This observation suggests that they may be an offspring or a subclass of the CPYC class of GRXs. We also find that the third position in the putative active centre of CCMC GRXs is occupied by an uncharged amino acid that is not necessarily a methionine residue, but can also be a branched amino acid. It is noteworthy that some GRXs that have, overall, higher sequence similarity to GRXs of the CPYC class contain active sites where the final cysteine residue has been replaced by other residues. This is summarized in Figure -5). The function of these proteins is unknown, and this may represent a situation where the GRX domain is being co-opted for a new function that has yet to be characterized.Figure Within each class of GRXs, different taxa cluster roughly as previously reported (see for example -28). For-10. They all contain a GRX-like putative active site sequence. The bacterial sequences in this cluster come from groups that are not typically considered as having GRXs  The highest homology between the Myxococcus xanthus and in the H. salinarium genomes [grx genes from H. salinarium and M. xanthus. We found that the codon usage in the CGFS class GRXs of Halobaterium is similar to the average codon usage in the Myxococcus genome. It is also similar to the codon usage in the Myxococcus CGFS class grx genes.b) The codon usage of genes is a characteristic that can often be used to identify HGT. This is so because the evolution of an organism leads to an optimization of the codon usage in genes for the specific physiology of that organism . We calc genomes . We alsogrx gene in H. salinarium are homologous to the flanking regions of the transposon gene XAC3504 from the gamma proteobacteria Xanthomonas axonopodis.c) The borders of the CGFS class grx genes in archaea could be degenerated palindromes. If this is so, it may indicate the remains of a degenerated transposon. Transposons are responsible for gene mobility within and between genes through HGT.d) The flanking regions of the CGFS class halobacteriales.Taken together, these observations suggest that CGFS class GRXs in archaea may have been the result of one HGT from some proteobacteria ancestor to the Unlike in archaea, single domain CGFS class and CPYC class GRXs are both widespread in bacteria, as shown in Figure Figure We compared the variability of the CPYC class alignments to that of the CGFS alignments. This variability can be quantified by calculating both, the average positional entropy of the alignment and the normalized mutual information (NMI) between each pair of positions in the alignment (see Methods for details).The higher the average positional entropy is, the higher the variability per position in the alignment is (see e.g. ). Based The results from NMI profiles support those from the averaged position entropy, although the interpretation of these profiles is more nuanced. On one hand, if two positions in the alignment have a NMI that is very high, one can interpret this result as indicating that any changes in the residue at one of the positions needs to be counterbalanced by a compensatory change in the residue of the other position -35. ThusAn alternative explanation for the differences in the variability between CPYC and CGFS GRXs is the following. The larger variability of CPYC GRXs could also be observed if CPYC class GRXs had an earlier origin than CGFS GRXs, because this could have allowed for CPYC GRXs to have evolved for a longer time. Our results suggest that this explanation is unlikely. In Figure As stated above, and summarized in Table Only the GRX-pyridine nucleotide disulphide oxireductase fusion and the TRX-GRX fusion are found in all three branches of the tree of life. All other multidomain proteins that contain a GRX domain are found only in specific branches of that tree Figure . For exaIn eukaryotes, most GRX domains in multidomain proteins are of the CGFS class Table . The exca) Proteins with a domain structure of the type peroxiredoxin-GRX, with the GRX domain being of the CPYC class. Peroxiredoxins are thiol dependent peroxidases involved in cell protection against oxidative stress.b) Proteins with a domain structure DUF296-GRX. DUF296 is a domain of unknown function that contains what appears to be a zinc finger like motif . This suS. cerevisiae Grx5 is implicated in mitochondrial maturation of iron-sulfur clusters [c) Proteins with a domain structure frataxin-rhodanese-GRX. Single domain frataxin proteins are involved in iron storage and metabolism and in iron-sulfur cluster biogenesis ,38. The clusters , this suHalobacteriales (archaea). Because GRXs are present in archaea, bacteria and eukaryotes, our results suggest that both the CPYC class and the CGFS class of GRXs were already present in the LCA. This inference follows from accepting the proposal that bacteria diverged first, followed by the divergence between archaea and eukaryotes [GRX domains are a part of the thioredoxin-fold superfamily. This superfamily includes domains of several classes, such as TRXs, PRXs (Peroxiredoxins), GSTs (glutathione S-transferase), GRXs, among others. Each of these domain classes is involved in different types of redox reactions that follow dissimilar mechanisms. In this work we analyzed GRX protein domains from a wide number of organisms in the tree of life. We confirm that GRXs are widespread over the three major kingdoms of life, both as individual proteins and as domains of larger proteins. We detect no signal of extensive HGT of GRXs among the different taxa, except for GRXs of the CGFS class between bacteria and karyotes . If one Our analysis of the available data leads us to speculate about the origin of GRXs. One should recall that GRXs and TRXs belong to the same protein super family because they have a common structural fold. In addition, when one uses BLAST to search for GRX sequence homologues in the UNIPROT database, we find TRX domains as the closest relatives of GRX domains (data not shown). Taking these two facts together, one could make the case that both types of domains may have originated from the same common ancestor gene. If this is so, then the clusters in Figure If the picture described in the previous paragraph is correct, CGFS-class GRXs would be the more specialized GRXs, which could entail having stronger functional constraints against mutations in their sequence. Our analysis finds that GRXs of the CGFS class indeed have a higher percentage of conserved residues than those of the CPYC class and that the average residue variability, over the stretches of the proteins where residue conservation is low, is similar in the CGFS and CPYC classes. This further supports the notion that the lower sequence diversity in the CGFS class may be due to this class having functional constraints on a larger set of residues than the CPYC class. A deeper understanding of the catalytic mechanisms of the two GRX classes and of the protein dynamics during catalysis would be necessary if one is to confirm this speculation and explain it in a mechanistically rational way. Nevertheless, enzymatic studies already indicate that the mechanism of action of both types of GRXs is different ,17.GRX modules as parts of multidomain proteins are widespread. Figure S. cerevisiae Grx3, the TRX domain seems to be required for the nuclear targeting of the molecule [The question arises on the biological advantages of such domain fusions. In the case of molecule , withoutmolecule , althougAn interesting observation is that while TRX-GRX proteins in eukaryotes have GRX modules of the CGFS class, TRX-GRX proteins in bacteria and archaea have GRX modules of the CPYC class. This is consistent with the fusion between TRX and GRX modules having occurred independently in evolution at least twice. Furthermore, the TRX-GRX fusion proteins in eukaryotes have undergone further evolution, giving rise to proteins where the GRX module has been duplicated once or twice. The observations are consistent with the following scenarios Figure :a) Scenario A: TRX-GRX fusion, with GRX belonging to the CPYC class, present at the LCA of the three kingdoms. TRX-GRX fusion lost in the eukaryotic branch, with a subsequent, independent, new TRX-GRX fusion event occurring in eukaryotes, this time with a GRX of the CGFS class.b) Scenario B: TRX-GRX fusion, with GRX belonging to the CPYC class, occurring in ancestral archaea, followed by HGT of this protein to the common ancestral of several bacterial lineages. Independent TRX-GRX fusion event occurring in eukaryotes, this time with a GRX of the CGFS class.c) Scenario C: TRX-GRX fusion, with GRX belonging to the CPYC class, occurring in ancestral bacteria, followed by horizontal gene transfer of this protein to the common ancestral of archaea. Independent TRX-GRX fusion event occurring in eukaryotes, this time with a GRX of the CGFS class.We do not have enough data to distinguish between the three hypotheses. However, Occam's razor suggests that scenario b) may be the most likley, because that is the scenario where a smaller number of events would have had to occur. This would point to the TRX-GRX hybrid proteins as an interesting example of convergent evolution in domain architecture.In this study we trace the origin of glutaredoxins to the LCA of archaea, bacteria and eukaryotes. We propose probable patterns of evolution for the different GRX classes and trace the origin and evolution of recombination events between the GRX domain and other protein domains. We find at an interesting case of convergent evolution in the domain architecture of TRX-GRX proteins.S. cerevisiae, Escherichia coli and Halobacterium salinarium. All cDNA sequences corresponding to the UNIPROT entries were retrieved from Genebank [We used the UNIPROT database  to retriGenebank . Once alBecause a large number of very similar sequences were identified, we used the "Decrease Redundancy" program at SWISSPROT  to reducMEGA4  was usedMultidomain proteins were identified using the Domain Fishing server  and PROSf represents the relative frequency of amino acid of type m in position i of the alignment and f represents the join relative frequency of that amino acid in position m and of amino acid of type k in position j of the alignment. The higher the covariance between any two positions, the higher the Mutual Information between those two positions will be. For representation purposes in Figure Max{MI} is the maximum MI between any two positions in the alignment. The higher NMI  is, the higher the covariance between positions i and j will be.Mutual information between different position pairs in an alignment is indicative of how much the residue variation in one position constrains the residue variation in the other position. It was calculated using the formula k in an alignment was calculated using the formula Pjk is the frequency of amino acid j in alignment position k.Positional entropy measures how high or low is the variability at a given alignment position. Positional entropy for position Mathematica.The ratio Ka/Ks, where Ka stands for non-synonymous substitutions and Ks stands for synonymous in the DNA can be used to compare how fast different proteins are evolving . We use GRX: Glutaredoxin; HGT: horizontal gene transfer; LCA: Last common ancestor; MI: Mutual information; NMI: Normalized mutual information; TRX: Thioredoxin.RA and EH conceived and designed the study. RA and EV executed the study. RA, EV, AS and EH carried out data analysis, wrote the manuscript, and approved the final version.GRX sequences from Archaea. UNIPROT links to the GRX sequences from archaea, together with protein and DNA alignments and links to other sequences that have over 90% sequence identity.Click here for fileGRX sequences from bacteria. UNIPROT links to the GRX sequences from bacteria, together with protein and DNA alignments and links to other sequences that have over 90% sequence identity.Click here for fileGRX sequences from eukaryotes. UNIPROT links to the GRX sequences from eukaryotes, together with protein and DNA alignments and links to other sequences that have over 90% sequence identity.Click here for fileAnalysis of CGFS-GRXs sequences from archaea. Contains the supplementary table I, with compiled information about CGFS class GRXs in archaea.Click here for fileSequences of GRX domains from multidomain proteins. UNIPROT links to the GRX sequences from multidomain proteins, together with protein and DNA alignments and links to other sequences that have over 90% sequence identity.Click here for fileAligned sequences of CPYC class GRX domains from multidomain proteins. Alignment used to build the phylogenetic trees.Click here for fileAligned sequences of CGFS-class GRX domains from multidomain proteins. Alignment used to build the phylogenetic trees.Click here for file


Transcriptional activation by the NorR bEBP is controlled by a regulatory GAF domain that represses the ATPase activity of the central AAA+ domain in the absence of nitric oxide. Here, we investigate the mechanism of interdomain repression in NorR by characterizing substitutions in the AAA+ domain that bypass repression by the regulatory domain. Most of these substitutions are located in the vicinity of the surface-exposed loops that engage σ54 during the ATP hydrolysis cycle or in the highly conserved GAFTGA motif that directly contacts σ54. Biochemical studies suggest that the bypass mutations in the GAFTGA loop do not influence the DNA binding properties of NorR or the assembly of higher order oligomers in the presence of enhancer DNA, and as expected these variants retain the ability to activate open complex formation in vitro. We identify a crucial arginine residue in the GAF domain that is essential for interdomain repression and demonstrate that hydrophobic substitutions at this position suppress the bypass phenotype of the GAFTGA substitutions. These observations suggest a novel mechanism for negative regulation in bEBPs in which the GAF domain targets the σ54-interaction surface to prevent access of the AAA+ domain to the sigma factor.Bacterial enhancer binding proteins (bEBPs) are specialized transcriptional activators that assemble as hexameric rings in their active forms and utilize ATP hydrolysis to remodel the conformation of RNA polymerase containing the alternative sigma factor σ The central AAA+ domain of bEBPs is responsible for ATP hydrolysis and the consequent remodelling of the σ54-RNA polymerase that enables isomerization of the promoter DNA complexes from the closed to the open form . In contrast to the prototypical σMany bEBPs contain an amino-terminal regulatory domain that stringently controls the activity of the central AAA+ domain either negatively or positively in response to environmental cues . Most bEnorVW genes in Escherichia coli that encode a flavorubredoxin and its associated NADH-dependent oxidoreductase respectively -responsive bEBP, NorR, is required for transcriptional activation of the 54-RNA polymerase. Our results suggest that the σ54-interaction surface in the AAA+ domain is a target for intramolecular repression by the GAF domain.To investigate mechanisms of interdomain regulation in NorR, we have used a random mutagenesis approach to screen for mutations in the AAA+ domain that enable escape from GAF domain-mediated repression. Surprisingly, we find that substitutions within the highly conserved GAFTGA motif and in residues predicted to influence nucleotide-dependent conformational changes in this loop prevent intramolecular repression by the GAF domain in the absence of the NO signal. We demonstrate that the GAFTGA substitutions neither influence the DNA binding function of NorR nor the enhancer DNA-dependent oligomerization of the AAA+ domain and that variant proteins remain competent to catalyse open complex formation by σ54. For example, the equivalent of E276 in PspF (E97) is located close to the base of the L1 loop and forms nucleotide-dependent interactions with R131  in the L2 loop that co-ordinate loop movements during ATP hydrolysis  mutagenesis was employed to create mutations that potentially disrupt repression of the AAA+ domain by the N-terminal (NO-sensing) GAF domain. This strategy produced mutant versions of NorR that had significant activity in cultures grown in the absence of an NO source, in contrast to wild-type NorR, which is activated by endogenous NO generated in the presence of potassium nitrate . In somedrolysis . This isormation . In addiin vivo . We observed that the affinity of NorRΔGAF for a 361 bp DNA fragment containing the three enhancer sites upstream of the norV promoter was not significantly influenced by the presence of the G266D and G266N substitutions  result in significant constitutive activity. Negatively charged residues and serine substitutions not only prevent negative control but also stimulate NorR activity beyond wild-type levels. R81D, R81N and R81E give rise to twofold to threefold more activity than NorRΔGAF.From the biochemical results presented thus far, it seems likely that the GAFTGA mutations do not bypass intramolecular repression solely on the basis of changes in oligomerization state. To gain more insight into the nature of the interactions between the GAF and AAA+ domains, we followed a genetic suppression strategy. In previous work, mutagenesis of conserved residues in the GAF domain identified the R81L change that allows partial escape from interdomain repression in NorR . In vivoSince the R81 residue appears to be critical for interdomain repression, we decided to investigate whether R81 is required for positioning the GAF domain in the vicinity of the GAFTGA motif. We observed that the R81L substitution suppresses the constitutive activity of the G266D mutant so that repression of the AAA+ domain is almost completely restored . Interes54 contact in the absence of the NO signal. Furthermore, the R81 residue is critical in maintaining repression and may be a key residue in mediating the transition from the ‘off’ to the ‘on’ state.Next, we wanted to determine whether the suppression of the G266D phenotype was dependent on the substitution made at the R81 position. Results show that only hydrophobic changes including R81L, V, I and F enable suppression . It is p54-interaction surface or in the conserved GAFTGA motif itself. This invokes a model whereby the GAF domain negatively regulates the AAA+ domain by preventing access of the L1 and L2 loops to σ54  upstream of the AAA+ domain and the G1341C mutation produced the SstII restriction site (CCGCGG) downstream. In all other cases, targeted mutagenesis of the norR sequence was carried out using a PCR method , 0.2 mM dNTPs, 1.5 mM MgCl2 and 5 units of enzyme in a final volume of 50 ml. The PCR products were purified, digested with MfeI and SstII and subsequently recloned into pMJB1 digested with the same enzymes. Ethanol precipitation followed by electroporation of the ligated mutant plasmid sample into DH5α was conducted and plasmid purification carried out before transformation of the sample into MH1003 (−1), chloramphenicol (30 µg ml−1), carbenicillin (100 µg ml−1) and kanamycin (50 µg ml−1). Constitutive mutants were identified based on the ability of the norR gene to produce a protein that can activate expression of a norV–lacZ fusion. In the absence of inducer, constitutive mutants activate expression of β-galactosidase that cleaves the Xgal substrate to produce a blue product.Random PCR mutagenesis was carried out with in vivo was measured by introducing wild-type and mutant plasmids into MH1003 a nor: : cat derivative of E. coli strain MC1000 with a lacZ reporter fusion to the norVW promoter inserted at the phage λ attachment site  transformed with the relevant construct was grown shaking at 250 r.p.m. at 30°C to an OD600 of 0.6. IPTG was then added to a final concentration of 1 mM and the cells left for 2–3 h before harvesting at 5000 r.p.m. Pellets were resuspended in buffer A  containing EDTA-free protease inhibitors (Roche) and the cells were broken by French pressure disruption (1000 psi) in two passes. The insoluble material was then removed by centrifugation at 15 000 r.p.m. for 30 min. The clarified supernatant was loaded onto two 1 ml HiTrap chelating HP columns, connected in series and charged with 100 mM nickel chloride. The columns were equilibrated with NorR buffer A. Protein was then eluted using NorR buffer B . To remove imidazole and to prevent precipitation, NorR containing fractions were loaded as quickly as possible onto a Superdex 200 16/60 column (Amersham Biosciences), pre-equlibrated in buffer C . NorR containing fractions were concentrated using Amicon Ultra (Millipore) centrifugal devices with a 30 kDa MWC, aliquoted and stored in buffer containing 100 mM Tris-Cl, 100 mM NaCl, 4 mM DTT and 40% glycerol at −80°C, until required.norR–norVW region blunt-end cloned into the SmaI site of pUC19 (Open complex and gel retardation assays were carried out as described previously (Open complexes were probed using potassium permanganate as described previously (−1) at each concentration was calculated using the equation: [(ΔOD340/Δt)/6220]*1 × 106 where t is the time-course of the experiment in minutes. Reactions were carried out both in the absence and presence of 5 nM of a 266 bp fragment of the norR–norVW intergenic region generated from the pNPTprom plasmid  as described previously (Samples (2 µl) from fractions eluted from gel filtration columns containing either G266DΔGAF–His alone or in complex with 266 bp dsDNA were absorbed onto glow-discharged continuous carbon grids (TAAB) and stained with 2% uranyl acetate. Data were collected at 35 000× magnification using a FEI Tecnai 12 electron microscope operating at 120 kV. Micrographs were recorded directly on a 1 k × 1 k CCD camera .


Novel protein domain stochastic duplication/innovation models that are independent of genome-specific features are used to interpret global trends of genome evolution. Protein domains can be used to study proteome evolution at a coarse scale. In particular, they are found on genomes with notable statistical distributions. It is known that the distribution of domains with a given topology follows a power law. We focus on a further aspect: these distributions, and the number of distinct topologies, follow collective trends, or scaling laws, depending on the total number of domains only, and not on genome-specific features.We present a stochastic duplication/innovation model, in the class of the so-called 'Chinese restaurant processes', that explains this observation with two universal parameters, representing a minimal number of domains and the relative weight of innovation to duplication. Furthermore, we study a model variant where new topologies are related to occurrence in genomic data, accounting for fold specificity.a priori of the specific evolutionary history of a genome. We interpret this as the concurrent effect of neutral and selective drives, which increase duplication and decrease innovation in larger and more complex genomes. The validity of our model would imply that the empirical observation of a small number of folds in nature may be a consequence of their evolution.Both models have general quantitative agreement with data from hundreds of genomes, which indicates that the domains of a genome are built with a combination of specificity and robust self-organizing phenomena. The latter are related to the basic evolutionary 'moves' of duplication and innovation, and give rise to the observed scaling laws,  The availability of many genome sequences provides us with abundant information, which is, however, very difficult to understand. As a consequence, it becomes very important to develop higher-level descriptions of the contents of a genome, in order to advance our global understanding of biological processes. At the level of the proteome, an effective scale of description is provided by protein domains . DomainsProtein domains are related to sets of sequences of the protein-coding part of genomes. Multiple sequences give rise to the same topology, so sequence diversity can be explained as a stochastic walk in the space of possible sequences. However, the choice of a specific sequence in this set might also fine-tune the function, activity and specificity of the inherent physico-chemical properties that characterize a topology ,7. The tIn particular, the sequences of two duplicate domains that diverged recently will be very similar, so one can also give a strictly evolutionary definition of protein domains  as region to measure the size of a genome, we make the following observations, which confirm and extend previous ones .The large-scale data stemming from this classification effort enable us to tackle the challenge of understanding the functional genomics of protein domains ,12-14. IF(n). This means that even genomes that are phylogenetically very distant, but have similar sizes, will have similar numbers of domain classes. This is the case, for example, of the enterobacterium Shigella flexneris, with 3,425 domains and 670 distinct domain topologies (giving rise to domain classes), and the distant alkaliphilic Bacillus Bacillus halodurans, with 3,406 domains and 637 domain classes. Furthermore, the curve F(n) is markedly sublinear with size  have 702 distinct domain classes, but n = 3,921 for the former and n = 7,817 for the latter. Note that although the number of domains is increasingly invariant with n, the number of proteins is linear in n. Hence, the number of different domain combinations in one protein expands, indicating that proteome complexity increasingly relies on combinatorics rather than on number of distinct domain topologies .The number of domain classes (or hits of distinct domains) concentrates around a curve e Figure , perhapsF of domain classes having j members (in a genome of size n) follows the power law ~ 1/jα1+, where the fitted exponent 1 + α typically lies between 1 and 2  with 222 occurrences.The populations of domain classes follow power law distributions. Stated mathematically, the number n  at large genome sizes.On the other hand, the common trend for the number of domain classes at a given genome size and the common behavior of the observed power laws in different organisms having the same size (observations 1-3), call for a unifying behavior in these distributions, which has not been addressed so far. Here, we define and relate to the data a non-stationary duplication-innovation model in the spirit of Gerstein and coworkers . ComparepO, the probability to duplicate an old domain (modeling gene duplication), and pN, the probability to add a new domain class with one member . Iteratively, either a domain is duplicated with the former probability or a new domain class is added with the latter.An illustration of the model and a table outlining the main parameters and observables are presented in Figure piO, this hypothesis requires that piO ∝ ki , where ki is the population of class i, that is, the probability of finding a domain of a particular class and duplicating it is proportional to the number of members of that class.An important feature of the duplication move is the (null) hypothesis that duplication of a domain has uniform probability along the genome and, thus, it is more probable to pick a domain of a larger class. This is a common feature with previous models . This hyn. As pointed out in . Here θ is the parameter representing a characteristic size n needed for the preferential attachment principle to set in, and defines the behavior of f(n) for vanishing n. α is the most important parameter, which sets the scaling of the duplication/innovation ratio , and since pN is asymptotically proportional to the class density f/n, it is harder to add a new domain class in a larger, or more heavily populated genome. As we will see, this implies pN/pO → 0 as n → ∞, corresponding to an increasingly subdominant influx of new fold classes at larger sizes. We will show that this choice reproduces the sublinear behavior for the number of classes and the power law distributions described in observations 1-3.where nd α ∈ 0,. Here θ This kind of model has previously been explored in a different context in the mathematical literature under the name of Pitman-Yor, or the Chinese restaurant process (CRP) -32. In tf, the number of tables or domain classes, ki the population of class i, and ni, the size at birth of class i. Rigorous results for the probability distribution of the fold usage vector  confirm the results of our scaling argument. It is important to note that in this stochastic process, large n limit values of quantities such as ki and f do not converge to numbers, but rather to random variables [We investigated this process using analytical asymptotic equations and simulations. The natural random variables involved in the process are ariables .Ki and F  at large n, writing simple 'mean-field' equations in the spirit of statistical physics, for continuous n. From the definition of the model, we obtain:Despite of this property, it is possible to understand the scaling of the averages andKi(ni) = 1, and F(0) = 1. Hence, for α ≠ 0:These equations have to be solved with initial conditions andα = 0:while, for F(n) is sublinear, in agreement with observation 1.These results imply that the expected asymptotic scaling of P = F/F(n) [j > Ki(n) implies ni > n*, with n* and the number of classes born before size n, P(Ki(n) > j) = F(n*)/F(n). P can be obtained by derivation of this function. For n, j → ∞, and j/n small, we find:The mean-field solution can be used to compute the asymptotics of ,n)/F(n) . This woα ≠ 0, andfor α = 0. The above formulas indicate that the average asymptotic behavior of the distribution of domain class populations is a power law with exponent between 1 and 2, in agreeement with observation 2.for pN, pO and gives a linearly increasing F(n) and a power law distribution with exponent larger than two for the domain classes . A comparative scheme of the asymptotic results is presented in Table m members (edges of the node) is introduced, and at the same time m domains are duplicated (the edges connecting old nodes to the new node).The trend of the model of Gerstein and coworkers can be found for constant n, the probability distributions generated by a CRP contain large finite-size effects that are relevant for the experimental genome sizes. In order to evaluate the behavior and estimate parameter values taking into account stochasticity and the small system sizes, we performed direct numerical simulations of different realizations of the stochastic process , and F for finite sizes, and, in particular, for values of n that are comparable to those of observed genomes. At the scales that are relevant for empirical data, finite-size corrections are substantial. Indeed, the asymptotic behavior is typically reached for sizes of the order of n ~ 106, where the predictions of the mean-field theory are confirmed.Going beyond the mean behavior for large sizes  Figures  and 2b,cn causes the observed drift in the fitted exponent described in observation 3 and shown in Figure Ki(n) ~ n.Comparing the histograms of domain occurrence of model and data, it becomes evident that the intrinsic cutoff set by α = 0 and a model with finite (and definite) α: while the slope of F(n) is more compatible with a model having α = 0, the slopes of the internal power law distribution of domain families P and their cutoff as a function of n is in closer agreement to a CRP with α between 0.5 and 0.7 . Here, we will consider simply the empirical probabilities of usage of domain families for 327 bacterial genomes in the SUPERFAMILY database  Figure . These oIn order to identify model domain classes with empirical ones, it is necessary to label them. We assign each of the labels a positive or negative weight, according to its empirical frequency measured in Figure In the modified model, not all classes are equal. The cost function introduces a significance to the index of the domain class, or a colored 'tablecloth' to the table of the Chinese restaurant. In other words, while the probability distributions in the model are symmetric by switching of labels in domain classes , this clα that better agree with the empirical behavior of the number of domain classes as a function of domain size F(n) are also those that generate the best slopes in the internal usage histograms F. Namely, the best α values are between 0.5 and 0.7. Furthermore, the cost function generates a critical value of n, above which F(n), the total number of domain families, becomes flat. This behavior agrees with the empirical data better than the asymptotically growing laws of the standard CRP model. A mean-field calculation of the same style as the one presented above predicts the existence of this plateau .Simulations and analytical calculations show that this modified model agrees very well with observed data. Figures F(n), which clearly shows that genomes tend to cluster on a common curve. This fact is remarkable, and extends previous observations. For example, while it is known that generally in bacteria horizontal transfer is more widespread than in eukaryotes, the common behavior of innovation and duplication depending on coding genome size only might be unexpected. The sublinear growth of number of domain families with genome size implies that addition of new domains is conditioned to genome size, and, in particular, that additions are rarer with increasing size.The model shows that the observed common features, or scaling laws, in the number and population of domain classes of organisms with similar proteome sizes can be explained by the basic evolutionary moves of innovation and duplication. This behavior can be divided into two distinct universal features. The first is the common scaling with genome size of the power laws representing the population distribution of domain classes in a genome. This was reported early on by Huynen and van Nimwegen , but waspN/pO. This feature is absent in the model of Gerstein and coworkers, which is the closest to our formalism. We have shown that this choice is generally due to the fact that pN is conditioned by genome size. Furthermore, we can argue on technical grounds that the choice of having constant pO and pN would be more artificial, as follows. If one had ki/n, the total probability pO would be one, since the total population n is the sum of the class populations ki, and there would not be innovation. In order to build up an innovation move, and thus pN > 0, one has to subtract small 'bits' of probability from pN has to be constant, the necessary choice is to take ki/n - pN/f, where f is the number of domain classes in the genome. This means that the probability of duplication for a member of one class would be awkwardly dependent on the total number of classes.Previous literature on modeling of large-scale domain usage concentrated on reproducing the observed power law behavior and did not consider the above-described common trends. In order to explain these trends, we introduce a size dependency in the ratio of innovation to duplication α and θ. One may suspect that this addition weakens the salient point of having a model with few universal parameters. On the other hand, an effective 'parameter-poor' model can reproduce the main results of the specific model, which just depend on the assumption of the existence of two sets of 'universal' versus 'contextual' domain classes, and can be obtained by adding only one extra relevant parameter, the fraction of universal domains. The detailed weight of each empirical class remains important for the possible use as a null model.Furthermore, we have addressed the role of specificity of domain classes, by considering a second model where each class has a specific identity, given by its empirical occurence in the genomes of the SUPERFAMILY data set. This model, which gives up the complete symmetry of domain classes, has the best quantitative agreement with the data, and is a good candidate for a null model designed for genome-scale studies of protein domains. Obviously, the better performance of this model variant has the cost of introducing extra phenomenological parameters, which, however, are not adjustable, but empirically fixed, since each class has its own value determined by its empirical occurrence. Thus, these extra per-class parameters do not need any estimation as n using the basic moves of duplication and innovation . Genomes from the same realization can be thought of as a trivial phylogenetic tree, where each value of n gives a new species. In contrast, independent realizations are completely unrelated.It is useful to spend a few words on the role of common ancestry in the observed scaling laws, compared to the model. Clearly, empirical genomes come from intertwined evolutionary paths. The model treated here does not include time in generations, but reproduces sets of 'random' different genomes, parameterized by size F at the same value of n. In other words, the predictions of the model are essentially the same for all histories (at fixed parameters), which can be taken as an indication that the basic moves are more important in establishing the observed global trends than the shared evolutionary history. This is confirmed by the data, where phylogenetically extremely distant bacteria with similar sizes have nevertheless very similar numbers and population distributions of domain classes.The scaling laws hold both for each realization and, more importantly, for different realizations, indicating that they are properties that stem from the fact that all branches of phylogenetic trees are built with the same basic moves and not from the fact that branches are intertwined. For example, two completely unrelated realizations will reach similar values of While the scaling laws are found independently on the realization of the CRP model, the uneven presence of domain classes can be seen as strongly dependent on common evolutionary history. Averaging over independent realizations, the prediction of the standard model would be that the frequency of occurrence of any domain class would be equal, as no class is assigned a specific label. In the Chinese restaurant metaphor, the customers only choose the tables on the basis of their population, and all the tables are equal for any other feature. However, if one considers a single realization, which is an extreme but comparatively more realistic description of common ancestry, the classes that appear first are obviously more common among the genomes. In particular, in the 'specific' variant of the model, the empirically ubiquitous classes are given a lower cost function, and tend to appear first in all realizations.This model has full quantitative descriptive value on the available data. Its value is also predictive, as removing a few genomes does not affect its power. However, it can be argued that this predictivity is trivial, as there is little biological interest in knowing that a genome behaves just as all the other ones. More interestingly, the model can be used negatively, to verify whether and to what extent a genome deviates from the expected behavior in its domain class composition and population. In other words, we believe that it could be an interesting tool to use as a null model in evolutionary studies of domains at the genome level.While domain deletion is a common phenomenon, we have chosen to consider (similarly to Gerstein and coworkers) a basic model including duplication and innovation moves only. Inspection of a variant of the model with domain deletion  shows that addition of domain loss does not change the basic results. Provided domain loss is not dominant , the extra parameter of domain deletion only determines a correction to the scaling exponents. Therefore, it can be considered a secondary ingredient to reproduce the scaling laws, and the basic model we consider is sufficient to establish the relevant behavior.The key limitation in the treatment we have performed is the assumption that gene loss is not dominant. While domain loss has been addressed and measured at large scales , no quann, they have to be added with constant probability, as in the model of Gerstein and coworkers [All sequenced genomes contain a large number of 'ORFan' proteins whose domains are not scored by domain databases because of the total lack or a very limited extent of homologs. If all these domains are thought to give rise to singleton domain classes, the observed scaling laws might be affected. In other words, classes corresponding to 'rare' domain topologies are harder to discover, and thus more likely not to be in the databases. This can create some bias in the data if these 'ORFans' do not behave as the observed domains. Assuming they do not, in order for their domain classes to increase linearly with oworkers . The avapN/pO as a function of proteome size n. As we have shown, this ratio must scale in the correct way with n in order to reproduce the data. As shown in Table α of the model. Precisely, the ratio pN/pO decreases like ~ nα-1. In other words, necessarily something affects the addition of domains with new structures relative to domains with old structures, making it sparser with increasing size. This fact is not a prediction of the model, but rather a feature of the data, which constrain the model. Note that innovation events can have the three basic interpretations of horizontal transfers carrying new domain classes, gene-genesis or splitting of domain classes when internal structures diverge greatly, while duplication events can be interpreted as real duplication, or horizontal transfers carrying domains that belong to domain classes already present in the genome. While this might be confusing if one focuses on the genome, it seems reasonable to associate these processes to true 'innovations' and 'duplications' at the protein level. At least for bacteria, innovation by horizontal transfer could be the most likely event. In this case, the question could be reduced to asking why the relative rate of horizontal transfer of exogenous domain classes decreases with proteome size relative to the sum of duplication and horizontal transfer of endogenous domain classes.The next question worth discussing is the possible biological interpretation of the scaling of innovation to duplication, pN/pO to decrease with n, either pO has to increase, or pN has to decrease, or both. A possible source of increase of p0 with n is the effective population size. Recent studies [In order for  studies  suggest  studies ,35. On tpN to decrease could be selective. New domains are only likely to be selected if they perform a biological function that is not covered by pre-existing domains or their combinations. Hence, as the number of domains increases, the chance a new one will be accepted should decrease. Along similar lines, we would like to suggest that a reason for pN to decrease with n could be related not only to function, but also to the cost for 'wiring' new domains into existing interaction networks. The argument is related to the so-called 'complexity hypothesis' for horizontal transfers [n domains (or for simplicity monodomain genes) and F domain families, the process leading to the acceptance of a new domain family, and thus to a new class of functions, will need a re-adaptation of the population of all the domain families causing an increase δn in the number of genes. This increase is due to an underlying optimization problem that has to adapt the new functions exploited by the acquired family to the existing ones (by rewiring and expanding different interaction networks). To state it another way, we imagine that in order to add δF new domain classes, or 'functions', it is necessary to insert δn new degrees of freedom ('genes') to be able to dispose of the functions. Now, generically, the computational cost for this optimization problem  could be a constant function of the size (and thus δn ~ δF), or else polynomial or exponential in F δF, respectively). Integrating these relations gives n ~ F in the first case, n ~ Fd+1 in the second, and n ~ exp(F) in the third. Inverting these expressions shows that the first choice leads to the linear scaling of the model of Gerstein and coworkers, while the second two correspond to the CRP, and to a sublinear F(n), which could follow a power law or logarithmic, depending on the computational cost. In other words, following this argument, accepting a new domain family becomes less likely with increasing number of already available domain families, as a consequence of a global constraint. This constraint comes from the trade-off between the advantage of incorporating new functions and the energetic or computational cost to govern them (both of which are related to selective pressure). This hypothesis could be tested by evaluating the rates of horizontal trasfers carrying new domain classes in an extensive phylogenetic analysis.Finally, another reason for ransfers -39, whicThe model and data together indicate that evolution acts conservatively on domain families, and shows increasing preference with genome size to exploiting available topologies rather than adding new ones. A final point can be made regarding the number of observed domains. The model assumes that the new domain classes are drawn from an infinite family of topologies, which can be even continuous , and leaWe considered data on protein domains on 327 bacteria, 75 eukaryotes, and 27 archaea from the SUPERFAMILY database .The quantitative duplication-innovation-loss evolutionary models were explored by mean-field theory and direct simulation.CRP: Chinese restaurant process.MCL designed and performed research, and wrote the paper. BB designed and performed research. AS and PH performed research. All authors read and approved the final manuscript.The following additional data are available with the online version of this paper. Additional data file Supplementary information on the model and data analysis.Click here for file


The mechanism by which the arthropod Oskar and vertebrate TDRD5/TDRD7 proteins nucleate or organize structurally related ribonucleoprotein (RNP) complexes, the polar granule and nuage, is poorly understood. Using sequence profile searches we identify a novel domain in these proteins that is widely conserved across eukaryotes and bacteria.Using contextual information from domain architectures, sequence-structure superpositions and available functional information we predict that this domain is likely to adopt the winged helix-turn-helix fold and bind RNA with a potential specificity for dsRNA. We show that in eukaryotes this domain is often combined in the same polypeptide with protein-protein- or lipid- interaction domains that might play a role in anchoring these proteins to specific cytoskeletal structures.Thus, proteins with this domain might have a key role in the recognition and localization of dsRNA, including miRNAs, rasiRNAs and piRNAs hybridized to their targets. In other cases, this domain is fused to ubiquitin-binding, E3 ligase and ubiquitin-like domains indicating a previously under-appreciated role for ubiquitination in regulating the assembly and stability of nuage-like RNP complexes. Both bacteria and eukaryotes encode a conserved family of proteins that combines this predicted RNA-binding domain with a previously uncharacterized domain (DUF88). We present evidence that it is an RNAse belonging to the superfamily that includes the 5'->3' nucleases, PIN and NYN domains and might be recruited to degrade certain RNAs.This article was reviewed by Sandor Pongor and Arcady Mushegian. Animal germ cells possess specialized ribonucleoprotein (RNP) granules termed nuage or germinal granules that appear as electron-dense fibrous and motile bodies localized to the cytoplasm -3. In seDrosophila, where the RNA-binding protein Oskar has been found to be a critical player in initiating the formation of polar granules [Nucleation of such RNP complexes has been extensively studied in granules ,8,9. In Drosophila polar granule protein Oskar showed that it contains a C-terminal catalytically inactive SGNH hydrolase domain [Drosophila protein CG8920 , vertebrate protein limkain b1 , the Arabidopsis protein AT2G15560 , proteins typified by TTHERM_00129230 from ciliates  and cgd2_2940 and its orthologs from apicomplexans . Some of these proteins, such as TDRD5, TDRD7 and Limkain b1 from vertebrates showed multiple tandem repeats of the homologous region that enabled us to precisely determine its boundaries  in a profile-profile comparison using the HHSEARCH program. PSI-BLAST and JACKHMMER searches recovered a bacterial representative NE0665 (gi: 30248674) from Nitrosomonas europaea, whose NMR structure has been determined as part of the structural genomics initiative  domain.Examination of this structure showed that the domain adopts a winged helix-turn-helix (wHTH) fold, which is characterized by a core 3-stranded HTH with a C-terminal extension of two strands. Structure prediction of just the eukaryotic versions using the JPRED program, which combines information from residue frequencies in columns, a HMM and a PSSM derived from the alignment, also predicted a secondary structure progression completely congruent with that observed in the above bacterial version. Based on these observations we named this novel conserved domain the e.g. Mbur_0520 Methanococcoides burtonii) that appear to be relatively late lateral transfers of bacterial versions. The bacterial and the eukaryotic versions can be distinguished based on their sequence conservation patterns  showed that it is a member of the 5'->3' nuclease domain superfamily that includes RNAses such as the PIN, NYN, and phage T4-type viral RNAse H domains [The OST-HTH superfamily is primarily found in bacteria and eukaryotes with very rare occurrences in archaea  [Eukaryotic members of the OST-HTH superfamily, other than those in Limkain b1, show a remarkable diversity of architectures Fig. . Versionlipases) ; howeverlipases) ,16.We represented the domain architectures of the OST-HTH as an ordered network where each node is a domain and each edge represents co-occurrence of two domains as immediate neighbors in the same polypeptide Fig. . This neNitrosomonas europaea NE0665) as a query. The best hit in this search was the wHTH domain of the archaeal replication protein CDC6 that binds dsDNA [Others and we have formerly characterized several other RNA-binding domains with the classical and circularly permuted versions of the wHTH fold . Exampleds dsDNA . Both thds dsDNA ,10, suggThalassiosira). These findings indicate the presence of robust RNAi machinery that might be specifically involved in chromatin level silencing as in other eukaryotes. Identification of several OST-HTH superfamily members in these eukaryotic lineages raises the possibility that they participate in the formation of RNP structures that are critical for counter-transposon defense. As in the case of the animal nuage/germinal granules these RNPs could also participate in sub-cellular localization of various RNAs in various eukaryotes. For example, in photosynthetic stramenopiles such as Aureococcus anophagefferens there are giant proteins in which the OST-HTH domain occurs with multiple distinct RNA-binding and ubiquitin E3 ligase domains in the same polypeptide and could function as large scaffolds for assembly of RNP complexes .Sequence profile searches were performed against the NCBI non-redundant (NR) database of protein sequences , and a locally compiled database of proteins from eukaryotes with completely or near-completely sequenced genomes. PSI-BLAST searches  were perThe authors declare that they have no competing interests.VA and LA were made the discovery and wrote the paper. DZ was performed the analysis on the LK-nuclease (DUF88) domain. All authors read and approved the final manuscript.Sandor Pongor, International Centre for Genetic Engineering and Biotechnology, Trieste, ItalyThe discovery of RNA regulatory mechanisms is one of the most fascinating insights of modern biology. RNP granules are especially difficult targets within this widespread and varied set of molecular scenarios because of their complex and presumably loosely defined molecular architecture is not easily amenable to structural studies. The mechanism by which RNP granules self-organize at specific cellular locations is currently poorly understood. The authors present a predictive bioinformatics analysis of the proteins of the polar granule and nuage complexes, based on sequence alignment, domain architecture analysis and sequence-structure superpositions and suggest that a hitherto unknown domain-type, OST-HTH, with a potential specificity for dsRNA may play a key role in the recruitment process that anchores nucleoprotein granules including miRNAs, rasiRNAs and piRNAs to specific cellular structures. The paper is clearly and carefully presented and the conclusion represents an important advance.1. The Materials and Methods section could be more detailed and more understandable for a wide audience. Minor: I did not find reference to JACKHMMER,Response: A detailed Materials and Methods in available as a part of Additional File 1Arcady Mushegian, Stowers Institute, Kansas City, United StatesI have no concerns about the validity of the sequence relationships and structural predictions described in this work. Several queries to the authors:"It is also possible that the nuage complex is related to other major RNP granules such as those found in neurons ." -- relResponse: The two RNPs indeed share several common proteins or those with homologous RNA-binding domains and similar architectures. Additionally, both neuronal RNPs and nuage-like complexes share other distinctive features: 1) A similar ultrastructure; 2) Presence of dsRNA; 3) intracellular motility. The motility of both these granules marks them as specialized elements required for active sub-cellular RNA localization as against passive aggregations of RNAs complexed with proteins.p.6 last paragraph: I do not think that the network shown in Fig. This point is in fact not so minor, as it concerns the explanatory and predictive utility of networks in biology.Response: The network in Fig. This file contains additional material and methods, data for phyletic patterns, domain architectures and alignments of OST-HTH and associated conserved domains.Click here for file


The von Willebrand Factor A (vWF A) domain is one of the most widely distributed structural modules in cell-matrix adhesive molecules such as intergrins and extracellular matrix proteins. Mutations in the vWF A domain of matrilin-3 cause multiple epiphyseal dysplasia (MED), however the pathological mechanism remains to be determined. Previously we showed that the vWF A domain in matrilin-1 mediates formation of a filamentous matrix network through metal-ion dependent adhesion sites in the domain. Here we show two new functions of the vWF A domain in cartilage-specific matrilins (1 and 3). First, vWF A domain regulates oligomerization of matrilins. Insertion of a vWF A domain into matrilin-3 converts the formation of a mixture of matrilin-3 tetramer, trimer, and dimer into a tetramer only, while deletion of a vWF A domain from matrilin-1 converts the formation of the native matrilin-1 trimer into a mixture of trimer and dimer. Second, the vWF A domain protects matrilin-1 from proteolysis. We identified a latent proteolytic site next to the vWF A2 domain in matrilin-1, which is sensitive to the inhibitors of matrix proteases. Deletion of the abutting vWF A domain results in degradation of matrilin-1, presumably by exposing the adjacent proteolytic site. In addition, we also confirmed the vWF A domain is vital for the secretion of matrilin-3. Secretion of the mutant matrilin-3 harbouring a point mutation within the vWF A domain, as occurred in MED patients, is markedly reduced and delayed, resulting from intracellular retention of the mutant matrilin-3. Taken together, our data suggest that different mutations/deletions of the vWF A domain in matrilins may lead to distinct pathological mechanisms due to the multiple functions of the vWF A domain. In cartilage, extracellular matrix (ECM) molecules mediate cell-matrix and matrix-matrix interactions, thereby providing tissue integrity. Matrilins (matn) are a novel ECM protein family which consists at least of four members . All theThe vWF A domain is one of the most widely distributed domains involved in cell adhesion and the formation of multiprotein complexes. These vMED is an osteochondrodysplasia primarily characterized by delayed and irregular ossification of the epiphyses and early-onset osteoarthritis . Two difTo determine these unknown roles of the vWF A domain in matrilins, we performed a series of deletions and mutations of the vWF A domain in cartilage-specific MATN-1 and -3. We found several novel functions of the vWF A domain of matrilins including regulation of protein secretion, oligomeric assembly, and proteolysis by matrix proteases.Full-length mouse matrilin-3 cDNA was cloned by RT-PCR from the RNA isolated from sternal cartilage of newborn mice. Total RNA was isolated using RNeasy kit (Qiagen). RT-PCR of matrilin-3 mRNA was performed using Titan one tube RT-PCR system  according to manufacturer's instruction. In brief, RNA (500 ng), dNTP (0.2 mM/each), DTT (5 mM), RNase inhibitor (5 unit), primers 0.4 μM/each), reaction buffer 1×), and enzyme mix (1 μl) were added in one tube and the volume adjusted to 50 μl. The reverse transcription were performed at 50°C for 30 min and then heated at 94°C for 2 min. Two step-PCR were used in the same tube with the following condition: 94°C 30 sec, 50°C 30 sec, and 68°C 1.5 min for 10 cycles, and then, the annealing temperature was raised to 55°C for another 20 cycles. The nucleotide sequence of matrilin-3 cDNA was confirmed by DNA sequencing. This cDNA and cDNAs encoding chicken matrilin-1 and -3 from previous studies [ μM/each,×, and encDNA constructs of matrilin-3 and -1 were transfected into COS-7 cells (Monkey Kidney Fibroblast Cells) or MCT cells   using LIWestern blot analysis was performed with collected conditioned medium or cell lysates from transfected cell culture. For non-reducing condition, collected samples were mixed with standard 2× SDS gel-loading buffer. For redCOS-1 or MCT cells were cultured in DMEM + 10% FBS in 12-well plates overnight. Matrilin-3 or MED-mutant matrilin-3 cDNA was transfected into the cells using Lipofectamin 2000 (Invitrogen). Three days after transfection, cells were starved for 2 hours in 0.5 ml cysteine and methionine free medium (Sigma), pulse-labeled in 100 μCi/ml medium of S-35 methionine (Amersham) for 1 hour, and chased in normal medium. After harvest of culture supernatants, monolayer cells were lysed in 1% NP-40, 50 mM Tris, pH 7.4. Immunoprecipitation was carried out by incubating culture supernatant or cell lysate with 1.5 μl anti-V5 antibody (Invitrogen) at 4°C for 2 hours, followed by coupling to protein A/G plus agarose (Santa Cruz) overnight at 4°C. After precipitation, the samples were eluted by boiling after washing 3 times with 0.5% Triton 100 in TBS. The eluted proteins were separated by electrophoresis in a 4–15% SDS-PAGE gel, followed by transferring to a PVDF membrane and exposed to X-ray films.After cells from Cos-1 and MCT cell lines were seeded onto 8-well chamber slides, 1 μg wild-type matrilin-3 or MED-mutant matrilin-3 cDNA was transfected into each well using Lipofectamin 2000 (Invitrogen). Three days after transfection, monolayer cells were fixed with 70% ethanol, 50 mM glycine for 1 hour. Immunofluorescence staining was performed by incubation of anti-V5 primary antibody (Invitrogen) at 1:200 for 2 hours, followed by incubation with donkey anti-mouse rhodamine secondary antibody (Jackson Laboratory) at 1:200 dilutions in the presence of Hoechst Stain Solution (Sigma). Slides were mounted with coverslips in Gel/Mount (Biomed).To understand the structure-function relationship of cartilage-specific matrilins: MATN1 and 3, a series of cDNAs containing mutations and deletions in MATN1 and 3 were constructed Fig. . The cDNBecause the amount of matn3 detected by western blot reflected the accumulation of matn3 due to both matn3 synthesis and degradation, we then chased secretion of radiolabelled matn3 after pulse-labelling its synthesis. Secretion of the mutant matn3 was greatly reduced than that of the wildtype matrilin-3 in MCT chondrocytes Fig. . In Cos To understand whether the vWFA domain plays a role in modulating matn3 oligomeric assembly, we inserted the vWFA2 domain from MATN1 into MATN3, which normally does not contain the vWFA2 domain Fig. . The secTo perform the converse experiment, we deleted the vWFA2 domain from wildtype MATN1 Fig. . While mThe presence of the 26 KD N-terminal peptide fragment suggests that there is a cleavage site at the junction between the vWFA2 domain and the coiled coil domain, which is responsible for matn1 processing. This junction consists of only four amino acid residues EEDP, which precedes the cysteine residues responsible for covalently link matrilin molecules in the coiled-coil domain Fig. . Δmatn-1To determine whether the coiled-coil domain also played a role in regulating matrilin assembly, we replaced the coiled coil domain in mini-matn-3 with the coiled-coil domain from matn-1 Fig. . InsteadOur study suggests that the matrilin vWF A domain, a widely distributed structural module in integrins and ECM proteins, plays a role in regulating protein secretion, assembly, and proteolysis, in addition to its well-documented role in cell-matrix adhesion . These nin vitro which is consistent with previous reports[We show that a single point mutation in the vWF A domain of mouse MATN3 (R116W), equivalent to the MED mutation (R121W) in human MATN3, leads to a deficiency of matrilin secretion s reports. In addis reports. BecauseAlthough matrilin-3 is the only matrilin family member that has been associated with chondrodysplasia so far, more and more point mutations within the vWF A domain of matrilin-3 have been reported to cause MED. They include mutations A219D, I192N, T120M, and E134K . It has The oligomeric assembly of matrilins is complex. This complexity is two fold. First, in contrast to some ECM protein families such as collagens that always form a trimeric structure, different matrilin member forms different set of oligomers. While the major oligomeric forms of matrilin-1, -2 and -4 are trimers, matrilin-3 is a tetramer . Second,We proposed an alternative theory that heterogeneity of oligomeric forms of matrilins may arise from imperfect oligomerization , in addiIn this study, we discovered a previously unsuspected latent proteolytic site in matrilin-1 between the vWF A domain and the coiled-coil domain. We found that, although wildtype matrilin-1 is not cleaved, deletion of the vWF A2 domain generates a cleaved peptide without the coiled-coil domain. The cleavage site was predicted to be in the junction region according to the molecular weight of the cleaved peptide. We confirmed the location of the cleavage site by deleting the junction region sequence EEDP, which eliminates processing Fig. . Based oBased on our current study and the studies from other laboratories ,27, we pOne of the major functions of the junction region containing these cleavage sites is to process matrilins and generate proteolytic fragments. The cleavage in the junction region of matrilins separates the vWF A domain that binds matrix ligands from the coiled-coil domain that oligomerizes matrilins. Such proteolytic cleavage may destabilize or destroy matrilin filamentous network in extracellular matrix. Our study raises a possibility that mutation/deletion of the vWF A domain may change its conformation to expose the mutant matrilin for accelerated proteolytic degradation.Different mutations/deletions of the vWF A domain in matrilins may lead to distinct pathological mechanisms due to the multiple functions of the vWF A domain. This may explain how different mutations within matrilin-3 lead to a variety of cartilage diseases.PAGE: polyacrylamide gel electrophoresis; RT-PCR: reverse-transcription polymerase chain reaction; MED: multiple epiphyseal dysplasia; COMP: cartilage oligomeric matrix proteinThe authors declare that they have no competing interests.YZ carried out the molecular genetic studies, participated in the sequence alignment, ZW carried out the proteolysis assays, JL participated in the immunocytochemistry, KK participated in the cloning of cDNA constructs, QC conceived the study, and participated in its design and coordination and drafted the manuscript. All authors read and approved the final manuscript.


Type II DNA topoisomerases (topos) are essential enzymes needed for the resolution of topological problems that occur during DNA metabolic processes. Topos carry out an ATP-dependent strand passage reaction whereby one double helix is passed through a transient break in another. Humans have two topoII isoforms, α and β, which while enzymatically similar are differentially expressed and regulated, and are thought to have different cellular roles. The C-terminal domain (CTD) of the enzyme has the most diversity, and has been implicated in regulation. We sought to investigate the impact of the CTD domain on activity.in vivo in a yeast system, and in vitro in activity assays. We find that the C-terminal domain of human topoII isoforms is needed for in vivo function of the enzyme, but not needed for cleavage activity. C-terminally truncated enzymes had similar strand passage activity to full length enzymes, but the presence of the opposite C-terminal domain had a large effect, with the topoIIα-CTD increasing activity, and the topoIIβ-CTD decreasing activity.We have investigated the role of the human topoII C-terminal domain by creating constructs encoding C-terminally truncated recombinant topoIIα and β and topoIIα+β-tail and topoIIβ+α-tail chimeric proteins. We then investigated function In vivo complementation data show that the topoIIα C-terminal domain is needed for growth, but the topoIIβ isoform is able to support low levels of growth without a C-terminal domain. This may indicate that topoIIβ has an additional localisation signal. In vitro data suggest that, while the lack of any C-terminal domain has little effect on activity, the presence of either the topoIIα or β C-terminal domain can affect strand passage activity. Data indicates that the topoIIβ-CTD may be a negative regulator. This is the first report of in vitro data with chimeric human topoIIs. Type II DNA topoisomerases (topos II) are essential enzymes that resolve topological problems with DNA that arise during processes such as DNA replication and transcription, and chromosome segregation. Their mechanism involves the passing of one DNA duplex through a transient covalent break in a second duplex, in an ATP-dependent reaction. Humans have two topoisomerase II isoforms, α and β, which, while similar, have distinct patterns of expression and are thought to have different cellular roles in vitro, the essential nature of the C-terminal domain is thought to be linked to regulation While topoII isoforms show a high degree of sequence homology, approximately 70% between human topoII α and β, this is mainly in the N-terminal three-quarters of the protein sequence where the two catalytic centres are located. The C-terminal quarter of the protein, while always highly charged, shows much more sequence diversity. The C-terminal domain has been shown to be vital for cell viability. However, as C-terminal truncations are active S. cerevisiae topoII Phosphorylation is a major form of regulation of human topoIIs, and has been shown to affect activity. Most modification sites are in the C-terminal domain, although a modification site at human topoIIα residue S29 that is a substrate for protein kinase C has also been identified Considering the human enzymes, phosphorylation sites have been identified in topoIIα, with casein kinase II (CKII) being a principle kinase. αS1524 was identified as a principle phosphorylation site S. cerevisiae indicating that the topoII major modification sites  again lie in the C-terminal domain S. cerevisiae topoII, SUMO modification has been linked to chromosome stability, with modified topoII enriched at centromeric regions Modification by SUMO  has also been linked to topoII regulation, with work in Work with human topo enzymes has shown that SUMO is rapidly conjugated to topoI, topoIIα and topoIIβ in response to DNA damage A major regulatory feature found in the C-terminal domains of topoIIs are nuclear localisation and nuclear export sequences (NLSs and NESs respectively). Without these signals, the enzyme is not able to localise to the nucleus, where it is essential during DNA replication, and cell viability is thus diminished or lost. Considering the human topoII isoforms, in topoIIα a strong NLS is found at 1454–1497 In human topoIIα an NES was initially localised to the region 1018–1088 in vivo found that the chimeric proteins, particularly those bearing the topoIIα C-terminal domain, could support growth Work with chimeric ‘tail swap’ proteins, where the C-terminal domain of topoIIα or topoIIβ is joined to the main body of the enzyme belonging to the opposite isoform, has been reported. A chimera of murine topoII consisting of the body of topoIIα and the tail of topoIIβ showed that this protein was unable to support growth in vitro and in vivo full length and C-terminally truncated forms of human topoIIα and β, and two ‘tail swap’ chimeric proteins where the C-terminal domain of each isoform is linked to the main sequence of the opposite isoform. In contrast to a recently published study describing the in vivo characterisation of tail swap proteins, where the C-terminal domain boundary was determined by alignment To assess whether the C-terminal domain, as the most diverse part of the protein, impacted the relative activities of topoIIα and β, we aimed to construct and characterise All chemicals were purchased from Sigma, BDH or Boehringer Mannheim. Restriction enzymes were purchased from NBL Gene Sciences Ltd, New England Biolabs, or Pharmacia Biotech. T4 Ligase was purchased from Gibco BRL. Etoposide was a gift from Prof. H. Newell, NICR, Newcastle, UK. mAMSA, Merbarone and Suramin were obtained from the Drug Synthesis and Chemistry branch, NCI, Bethesda, MD. Quercetin, Quercetagetin, Myricetin and Baicalein were provided by Prof. L.M. Fisher. mAMCA, DACA and Cl-DACA were provided by Prof. B Baguley, Auckland Cancer Society, New Zealand. All other cytotoxics were purchased from Sigma.S. cerevisiae strain JEL1 was used for overexpression of proteins. Yeast strain JN394t2-4, a temperature sensitive strain that is viable at 25°C but non-viable at 35°, was used in complementation analysis.E. coli pBR322 are also present. Plasmid YEpWob6, used to express recombinant human topoIIα, encodes the first 5 amino acids of S. cerevisiae topoII fused to residues 29–1531 of human topoIIα. Plasmid YEphTOP2β encodes recombinant human topoIIβ with the S165R mutation, with residues 46–1621 fused to the first 5 amino acids of S. cerevisiae topoII S. cerevisiae topoII. Plasmid intermediates used in the cloning process to construct C-terminal truncations and tail swaps are described in the ‘Results’ section and figure legends.All of the plasmids encoding topoII isoforms express protein under the control of the GAL1 promoter, and have a URA3 marker gene, the yeast 2μ plasmid replication origin and the β-lactamase gene and replication origin of Plasmids encoding truncated topoIIα and topoIIβ, as well as two ‘tail swap’ chimeric proteins with the opposite C-terminal domain fused to the main coding sequence were constructed as described in ‘Results’. In all cases restriction digests were carried out according to manufacturer's instructions. Fragments were separated by agarose gel electrophoresis and then purified using a QIAquick Gel extraction spin column. Ligations were then carried out using T4 ligase and the manufacturer's buffers, incubating with 0.5mM ATP for 16 hours at 4°C.Tail swap mutants were constructed with triple cloning procedures, then the junction sites were confirmed by sequencing both strands with dideoxy DNA sequencing using appropriate primers and a Sequenase version 2.0 DNA sequencing kit (Amersham).Recombinant human topoIIα and β proteins were expressed and purified as described previously Decatenation assays and cleavage assays with an end-labelled 4.3 kb linear DNA fragment from pBR322 were done as described previously t2-4, and plasmids encoding topoIIα and topoIIβ (WT and S165R) full length, C-terminally truncated or chimeric proteins. Yeast were grown in Ura- selective media at the permissive temperature (25°C) to an OD600 of 1, and then serially diluted in sterile microtitre trays. These cultures were then transferred to plates with an aluminium replicator, then incubated at the permissive, semi-permissive and non-permissive  temperatures respectively on glucose containing media, then growth was scored.Complementation assays were carried out in a temperature sensitive yeast strain JN394Truncations at the 3′ end of the coding sequence of topoIIα and topoIIβ (S165R) were constructed from plasmids YEpWob6 and YEphTOP2β respectively. The truncated topoIIα plasmid encodes residues 29–1242 and the truncated topoIIβ plasmid encodes residues 46–1263, these being the start of the C-terminal domains as determined by limited proteolysis experiments In the construction of C-terminally truncated topoIIα, PCR was used to introduce a PstI restriction site in the human topoIIα coding sequence and then to generate the full coding sequence. A fragment was generated between codon 791 (over a KpnI site) and codon 1244 (over the PstI site introduced above) of topoIIα. The PCR product was cloned into a Bluescript plasmid with a XhoI site immediately 3′ to the 792–1242 fragment, then excised by digestion with KpnI and XhoI. This was then cloned into the YEpWob6 plasmid, replacing the fragment 792–1531.In the construction of C-terminally truncated topoIIβ, multiple internal restriction sites in the topoIIβ sequence meant that a complex cloning procedure was necessary. A fragment containing topoIIβ residues 900–1263 was excised and cloned into a Bluescript plasmid between BamHI and PstI restriction sites, this having a XhoI site 36 residues downstream of the PstI site. A fragment between BamHI to the XhoI beginning at codon 900 was excised and cloned into a vector containing topoIIβ codons 46–899 plus the YEp backbone.Plasmids encoding chimeric ‘tail-swap’ proteins were created using a triple ligation approach and PCR to generate unique sites. Construction of the topoIIα+β tail plasmid, encoding topoIIα residues 30–1244 fused to topoIIβ residues 1263–1621, is illustrated in All topoIIβ constructs containing the S165R mutation were changed to give wild type sequence by site directed mutagenesis using a Chameleon kit (stratagene) according to manufacturer's instructions.50), in ng of protein, are shown in 50 between topoIIα and its C-terminal truncation, with values of 4.5±1.3 and 6±1 ng of protein respectively. The topoIIα+β tail chimera however does show a significant reduction in decatenation as compared to full length topoIIα, with a D50 of 29±1 (p = 0.0008 in a two-tailed unpaired student t-test). This implies that while topoIIα can function perfectly well without a C-terminal domain, the β-tail on the topoIIα enzyme impedes activity.The decatenation activity of wild type topoIIα, C-terminally truncated topoIIα, and topoIIα+β tail was assayed. The values for 50% decatenation +α tail would be expected to have still lower decatenation activity than topoIIβ(S165R). As shown in 50 values of 50±8 and 60±8 ng protein for topoIIβ(S165R) and C-terminally truncated topoIIβ(S165R) respectively. The activity of the topoIIβ(S165R)+α tail chimera was increased very slightly with a D50 of 41.5±0.5 ng protein, however this difference was not statistically significant , although the levels of growth differ, perhaps because of differences in the experimental systems or the sensitivity of methods in vitro decatenation activity as compared to their full length counterparts suggesting that the C-terminal domain is not necessary for in vitro activity, which is consistent with previous data The decatenation data imply that the topoII C-terminal domain is involved in the modulation of catalytic activity in the two human isoforms. The truncated topoII proteins had no difference in The regulation of catalytic activity by the C-terminal domain could be mediated via differential modification, for instance phosphorylation or SUMOylation, or could be linked to the extensive differences in primary sequence between the two C-terminal domains.Observations reported previously support the hypothesis that topoIIα and β C-terminal domains are important in differential regulation of the isoforms. All of the SUMO modification sites identified to date have been located in the C-terminal domain of topoII An analysis of the theoretical protein parameters of full length and truncated topoIIα and topoIIβ, and their tail swap derivatives, is shown in Cleavage data suggests that the C-terminal domain is not generally involved in cleavage, although there was a consistent, yet non-significant, increase in cleavage with the topoIIα derived proteins. Most drugs showed no difference in drug-stimulated cleavage patterns between topoIIα and β, implying that the C-terminal domain has no impact on the action of these drugs, consistent with previous work showing that topoIIα and topoIIβ cleave at similar sites In summary, we report the construction of C-terminally truncated and chimeric human topoII enzymes, and show that the C-terminal domain impacts on the activity of the two human isoforms. Further characterisation of human topoIIα and topoIIβ, perhaps by investigating the effect of SUMOylation on either isoform, or the cellular localisation of these tail swap proteins, will be needed to elucidate their different interactions with DNA substrates and functional roles in cells.


Anabaena sensory rhodopsin transducer (ASRT) is a small protein that has been claimed to function as a signaling molecule downstream of the cyanobacterial sensory rhodopsin. However, orthologs of ASRT have been detected in several bacteria that lack rhodopsin, raising questions about the generality of this function. Using sequence profile searches we show that ASRT defines a novel superfamily of β-sandwich fold domains. Through contextual inference based on domain architectures and predicted operons and structural analysis we present strong evidence that these domains bind small molecules, most probably sugars. We propose that the intracellular versions like ASRT probably participate as sensors that regulate a diverse range of sugar metabolism operons or even the light sensory behavior in Anabaena by binding sugars or related metabolites. We also show that one of the extracellular versions define a predicted sugar-binding structure in a novel cell-surface lipoprotein found across actinobacteria, including several pathogens such as Tropheryma, Actinomyces and Thermobifida. The analysis of this superfamily also provides new data to investigate the evolution of carbohydrate binding modes in β-sandwich domains with very different topologies.The Reviewers: This article was reviewed by M. Madan Babu and Mark A. Ragan. Anabaena, which utilizes a chlorophyll-based photosynthetic apparatus, was proposed to function as a sensory rhodopsin, as opposed to being a proton pump [Anabaena sensory rhodopsin (ASR) was based on several features [Thermotoga maritma [Anabaena. This prompted us to systematically investigate ASRT homologs with the view of gleaning new functional information regarding this family by means of comparative genomics analysis. As a consequence we show that ASRT defines a novel family of prokaryotic small-molecule-binding domains that function in a wide range of contexts, predominantly as a carbohydrate sensor.In the past decade membrane-embedded photoactive retinylidene-containing rhodopsins have been identified in several bacteria . One sucton pump -4. Inferfeatures , includifeatures ,5 and wa2II7) shows that the entire protein is comprised of a single globular domain with an eight-stranded β-sandwich fold [Thermotoga maritma ASRT ortholog (PDB: 1NC7) against NR database detected segments of putative secreted amidases from certain chloroflexi with e-values of borderline significance (e = 0.013) and then converged. These alignments corresponded to regions that did not overlap with the amidase catalytic domain and did not correspond to any previously described domains. These segments in the amidases were also independently detected in a search with the ASRT alignment as a HMM against the NR database using the recently released HMMER3 program (e = .024). Despite their borderline e-values, the alignment with the ASRT starting point extended throughout the entire globular domain in the latter and showed conservation of structurally critical hydrophobic residues. To test this relationship we performed a search with the above-detected sequence segments from the amidases against a library of HMMs derived from PDB structures as seeds using HHpred, which performs profile-profile comparisons, and recovered the Anabaena ASRT and its Thermotoga orthologs as the best hits with significant e-values (E = 10-3). Likewise, a reciprocal PSI-BLAST search initiated with one of these regions detected in the amidases  identified Anabaena ASRT and its Thermotoga orthologs  and in subsequent iterations retrieved all known ASRT homologs. This search also detected multiple repeats of the segment related to ASRT in the Roseiflexus amidase-domain-containing protein. In further transitive searches using representatives of these additional segments as query , we retrieved, in addition to the previously identified homologs, sequences from actinobacteria such as Tropheryma whipplei. Reciprocal PSI-BLAST searches with representatives of the segments detected in these actinobacterial sequences (e.g. gi:28493092) retrieved several other actinobacterial sequences together with representatives of sequences found in the initial searches . Hereinafter, we refer to this domain as the ASRAH (for Anabaena sensory ahodopsin- associated omology) domain.The 3D structure of ASRT (PDB: ich fold . All preich fold ) from valog PDB: NC7 againThermotoga and Anabaena in some actinobacteria, proteobacteria, firmicutes, Chthoniobacter flavus (verrucomicrobia), the extremely thermophilic Dictyoglomus [Natrialba magadii. The second family is present in secreted proteins, always fused to an amidase domain, and is predominantly found in photosynthetic bacteria such as Roseiflexus, Chloroflexus and Herpetosiphon. The third family, also secreted, is found mainly in actinobacteria and is defined by unique N- and C-terminal conserved extensions flanking the ASRAH domains. A multiple sequence alignment of the ASRAH domain was generated by editing a preliminary alignment produced by the KALIGN program based on PSI-BLAST HSPs and secondary structure predictions . Superposition of the secondary structure of this protein onto the alignment of the ASRAH superfamily shows that the sequence conservation is comprised predominantly of hydrophobic residues defining the core that stabilizes the β-sandwich. However, there are a few residues that distinguish this fold from other previously characterized β-sandwich folds. These include: 1) a well-conserved tryptophan, usually following a polar residue, present at the start of the first strand. This tryptophan appears to be central to a hydrophobic interaction required to hold the two β-sheets of the sandwich together  A neRhodothermus marinus [Thermotoga exists as a tetramer with each unit containing a deep cleft that could potentially form a binding-pocket on one face of the sheet. In two of the monomers in the structure we observed that the pocket contains a 1,2-ethanediol molecule , pyruvate decarboxylase/oxidase, a sugar/sugar acid dehydratase/racemase and a FAD-dependent oxidoreductase related to the glycolate oxidase  supporting the functional linkage between these proteins. Thus, these cell-surface proteins also display contextual connections that are compatible with them binding sugars. It is likely that they are lipid-modified themselves and form an actinobacteria-specific cell-surface structure by binding a polysaccharide created by the linked glycosyltransferase or recruiting the same enzyme to a precursor polysaccharide.We sought to obtain further evidence for the ligand-binding role of the ASRAH domains based on their domain architectures and predicted operonic associations. The predicted gene neighborhoods of the solo versions of the ASRAH domain show multiple associations with genes encoding various carbohydrate metabolism proteins. One gene neighborhood conserved across many phylogenetically distant bacteria, including ide Fig. . ASRT-liase Fig. . Intereslipobox" . They adNostoc, might represent a novel mechanism in which the behavior of a light sensor (ASR) is influenced via interaction with an intracellular sensor of a sugar or a related metabolite (ASRT). It is plausible that this interaction might have a role in phototaxis in response to intracellular nutrient status.Thus, the contextual evidence, combined with the structural evidence for ligand-binding, favors the ASRAH domain being a sugar-binding domain, in the manner of many other β-sandwich structures. This is not unexpected for the secreted or cell-surface versions of the ASRAH domain because it is consistent with the function of many other extracellular β-sandwich structures in binding cell-surface polysaccharides, which are parts of the peptidoglycan, glycoprotein and other polymeric carbohydrate layers that decorate prokaryotic cell surfaces. However, the intracellular standalone ASRAH domains are somewhat functionally unexpected because they appear to represent a novel regulatory mechanism - a potential sugar-sensor that might influence the function of other enzymes or sugar transporters encoded by the conserved gene-neighborhood via physical interactions with them depending on sugar concentrations. In light of this, we propose that the unusual linkage to the rhodopsin, which is observed only in the cyanobacterium Tropheryma, Actinomyces and Thermobifida. On the other hand, the identification of such a function in an intracellular context is of interest especially because the tetramer-forming standalone versions are predicted to regulate a diverse range of sugar metabolism operons or even the light sensory behavior in a cyanobacterium. This observation points to a previously unreported mechanism of regulation by a potential standalone small-molecular sensor that probably occurs at the level of protein-protein interactions rather than via the sensor domain of a one-component system transcription factor. In this respect such a regulatory process is closer to the allosteric regulation by small molecules.Our investigation demonstrates that ASRT belongs to a superfamily of domains predicted to bind small molecules, most likely sugars, in both extracellular and intracellular locations in various bacterial and few archaeal proteins. On one hand the presence of sugar binding capability in a β-sandwich scaffold is hardly unprecedented for domains found in extracellular or cell-surface proteins. Nevertheless, the identification of such a potential sugar-binding element in a novel cell-surface lipoprotein is of interest especially given its presence across actinobacteria, including several pathogens such as While "sideways" ligand binding via one of the exposed sheets has been observed in several β-sandwich scaffolds (e.g. DOMON domain and other carbohydrate-binding domains ), the exGene neighborhoods were determined using a custom script that uses completely sequenced genomes or whole genome shotgun sequences to derive a table of gene neighbors centered on a query gene. Then the BLASTCLUST program is used to cluster products in the neighborhood and establish conserved co-occurring genes. These conserved gene neighborhoods are then sorted as per a ranking scheme based on occurrence in at least one other phylogenetically distinct lineage ("phylum" in NCBI Taxonomy database), complete conservation in a particular lineage ("phylum") and physical closeness on the chromosome indicating sharing of regulatory -10 and -35 elements. Profile searches were conducted using the PSI-BLAST program  with a dThe authors declare that they have no competing interests.LMI and LA were involved in the discovery process. RdeS and LA performed the analysis. RdeS and LA wrote the paper. The figures were prepared by RdeS and LMI. All authors have read and approved the final manuscript.M. Madan Babu, MRC Laboratory of Molecular Biology, University of Cambridge, UK.Anabena sensory rhodopsin transducer. Through a rigorous computational analysis the authors first identified homologs of the ASRT gene in several bacteria that lack a sensory rhodopsin. Through a combination of genomic context and structural analysis, the authors report that this domain is likely to bind to small molecules, which are most likely to be sugars. In addition, the authors identify a subset of such proteins that are predicted to be secreted or membrane associated via lipid modification in several actinobacteria species, which also includes certain pathogens. Additional file In this manuscript, De Souza, Iyer and Aravind report the characterization of a family of proteins which are related to the 1. It is currently unclear how the authors identified secreted proteins and the membrane associated proteins. Could the authors clarify this point, please? In addition, it would be good to see a comment on the functional significance of secreting sugar binding proteins rather than having them membrane associated.Frankia sp. homolog, which is fused to glycosyltransferase, all proteins with signal peptides (dyads and tetrads) did not have transmembrane regions and, therefore, are probably secreted. The functional significance of secreting sugar-binding proteins: these sugar binding domains in the extracellular proteins are likely to provide a means for associating with the sugar moieties in extracellular biopolymers such as peptidoglycans and other glycans present in surface capsules and gums.Secreted proteins where identified based on detection of an amino-terminal signal peptide by the program SignalP, followed by manual inspection. Transmembrane regions were detected using TMHMM. Except for the Mark A. Ragan, Institute for Molecular Bioscience, The University of QueenslandBrisbane, Australia.I support the publication of your manuscript "The Anabaena sensory rhodopsin transducer defines a novel superfamily of prokaryotic small-molecule binding domains", by RF De Souza, LM Iyer and yourself, in Biology Direct as a Discovery Note.Supplementary material. Material and methods and a complete list of conserved gene neighborhoods and comprehensive alignment of the: .Click here for file