Rebecca Hamer

A maternally inherited autosomal point mutation in human phospholipase C zeta (PLCζ) leads to male infertility

BACKGROUND Male factor and idiopathic infertility contribute significantly to global infertility, with abnormal testicular gene expression considered to be a major cause. Certain types of male infertility are caused by failure of the sperm to activate the oocyte, a process normally regulated by calcium oscillations, thought to be induced by a sperm-specific phospholipase C, PLCzeta (PLCζ). Previously, we identified a point mutation in an infertile male resulting in the substitution of histidine for proline at position 398 of the protein sequence (PLCζ(H398P)), leading to abnormal PLCζ function and infertility. METHODS AND RESULTS Here, using a combination of direct-sequencing and mini-sequencing of the PLCζ gene from the patient and his family, we report the identification of a second PLCζ mutation in the same patient resulting in a histidine to leucine substitution at position 233 (PLCζ(H233L)), which is predicted to disrupt local protein interactions in a manner similar to PLCζ(H398P) and was shown to exhibit abnormal calcium oscillatory ability following predictive 3D modelling and cRNA injection in mouse oocytes respectively. We show that PLCζ(H233L) and PLCζ(H398P) exist on distinct parental chromosomes, the former inherited from the patients mother and the latter from his father. Neither mutation was detected utilizing custom-made single-nucleotide polymorphism assays in 100 fertile males and females, or 8 infertile males with characterized oocyte activation deficiency. CONCLUSIONS Collectively, our findings provide further evidence regarding the importance of PLCζ at oocyte activation and forms of male infertility where this is deficient. Additionally, we show that the inheritance patterns underlying male infertility are more complex than previously thought and may involve maternal mechanisms.

Cytochrome c biogenesis System I

Cytochromes c are widespread respiratory proteins characterized by the covalent attachment of heme. The formation of c‐type cytochromes requires, in all but a few exceptional cases, the formation of two thioether bonds between the two cysteine sulfurs in a –CXXCH– motif in the protein and the vinyl groups of heme. The vinyl groups of the heme are not particularly activated and therefore the addition reaction does not physiologically occur spontaneously in cells. There are several diverse post‐translational modification systems for forming these bonds. Here, we describe the complex multiprotein cytochrome c maturation (Ccm) system (in Escherichia coli comprising the proteins CcmABCDEFGH), also called System I, that performs the heme attachment. System I is found in plant mitochondria, archaea and many Gram‐negative bacteria; the systems found in other organisms and organelles are described elsewhere in this minireview series.

Deciphering chemotaxis pathways using cross species comparisons

BackgroundChemotaxis is the process by which motile bacteria sense their chemical environment and move towards more favourable conditions. Escherichia coli utilises a single sensory pathway, but little is known about signalling pathways in species with more complex systems.ResultsTo investigate whether chemotaxis pathways in other bacteria follow the E. coli paradigm, we analysed 206 species encoding at least 1 homologue of each of the 5 core chemotaxis proteins (CheA, CheB, CheR, CheW and CheY). 61 species encode more than one of all of these 5 proteins, suggesting they have multiple chemotaxis pathways. Operon information is not available for most bacteria, so we developed a novel statistical approach to cluster che genes into putative operons. Using operon-based models, we reconstructed putative chemotaxis pathways for all 206 species. We show that cheA-cheW and cheR-cheB have strong preferences to occur in the same operon as two-gene blocks, which may reflect a functional requirement for co-transcription. However, other che genes, most notably cheY, are more dispersed on the genome. Comparison of our operons with shuffled equivalents demonstrates that specific patterns of genomic location may be a determining factor for the observed in vivo chemotaxis pathways.We then examined the chemotaxis pathways of Rhodobacter sphaeroides. Here, the PpfA protein is known to be critical for correct partitioning of proteins in the cytoplasmically-localised pathway. We found ppfA in che operons of many species, suggesting that partitioning of cytoplasmic Che protein clusters is common. We also examined the apparently non-typical chemotaxis components, CheA3, CheA4 and CheY6. We found that though variants of CheA proteins are rare, the CheY6 variant may be a common type of CheY, with a significantly disordered C-terminal region which may be functionally significant.ConclusionsWe find that many bacterial species potentially have multiple chemotaxis pathways, with grouping of che genes into operons likely to be a major factor in keeping signalling pathways distinct. Gene order is highly conserved with cheA-cheW and cheR-cheB blocks, perhaps reflecting functional linkage. CheY behaves differently to other Che proteins, both in its genomic location and its putative protein interactions, which should be considered when modelling chemotaxis pathways.

Specificity of localization and phosphotransfer in the CheA proteins of Rhodobacter sphaeroides

Specificity of protein–protein interactions plays a vital role in signal transduction. The chemosensory pathway of Rhodobacter sphaeroides comprises multiple homologues of chemotaxis proteins characterized in organisms such as Escherichia coli. Three CheA homologues are essential for chemotaxis in R. sphaeroides under laboratory conditions. These CheAs are differentially localized to two chemosensory clusters, one at the cell pole and one in the cytoplasm. The polar CheA, CheA2, has the same domain structure as E. coli CheA and can phosphorylate all R. sphaeroides chemotaxis response regulators. CheA3 and CheA4 independently localize to the cytoplasmic cluster; each protein has a subset of the CheA domains, with CheA3 phosphorylating CheA4 together making a functional CheA protein. Interestingly, CheA3‐P can only phosphorylate two response regulators, CheY6 and CheB2. R. sphaeroides CheAs exhibit two interesting differences in specificity: (i) the response regulators that they phosphorylate and (ii) the chemosensory cluster to which they localize. Using a domain‐swapping approach we investigated the role of the P1 and P5 CheA domains in determining these specificities. We show that the P1 domain is sufficient to determine which response regulators will be phosphorylated in vitro while the P5 domain is sufficient to localize the CheAs to a specific chemosensory cluster.

i-Patch: Interprotein contact prediction using local network information

Biological processes are commonly controlled by precise protein‐protein interactions. These connections rely on specific amino acids at the binding interfaces. Here we predict the binding residues of such interprotein complexes. We have developed a suite of methods, i‐Patch, which predict the interprotein contact sites by considering the two proteins as a network, with residues as nodes and contacts as edges. i‐Patch starts with two proteins, A and B, which are assumed to interact, but for which the structure of the complex is not available. However, we assume that for each protein, we have a reference structure and a multiple sequence alignment of homologues. i‐Patch then uses the propensities of patches of residues to interact, to predict interprotein contact sites. i‐Patch outperforms several other tested algorithms for prediction of interprotein contact sites. It gives 59% precision with 20% recall on a blind test set of 31 protein pairs. Combining the i‐Patch scores with an existing correlated mutation algorithm, McBASC, using a logistic model gave little improvement. Results from a case study, on bacterial chemotaxis protein complexes, demonstrate that our predictions can identify contact residues, as well as suggesting unknown interfaces in multiprotein complexes. Proteins 2010.

Local network patterns in protein-protein interfaces.

Protein-protein interfaces hold the key to understanding protein-protein interactions. In this paper we investigated local interaction network patterns beyond pair-wise contact sites by considering interfaces as contact networks among residues. A contact site was defined as any residue on the surface of one protein which was in contact with a residue on the surface of another protein. We labeled the sub-graphs of these contact networks by their amino acid types. The observed distributions of these labeled sub-graphs were compared with the corresponding background distributions and the results suggested that there were preferred chemical patterns of closely packed residues at the interface. These preferred patterns point to biological constraints on physical proximity between those residues on one protein which were involved in binding to residues which were close on the interacting partner. Interaction interfaces were far from random and contain information beyond pairs and triangles. To illustrate the possible application of the local network patterns observed, we introduced a signature method, called iScore, based on these local patterns to assess interface predictions. On our data sets iScore achieved 83.6% specificity with 82% sensitivity.

Predicting Inter-Species Cross-Talk in Two-Component Signalling Systems

Phosphosignalling pathways are an attractive option for the synthetic biologist looking for a wide repertoire of modular components from which to build. We demonstrate that two-component systems can be used in synthetic biology. However, their potential is limited by the fact that host cells contain many of their own phosphosignalling pathways and these may interact with, and cross-talk to, the introduced synthetic components. In this paper we also demonstrate a simple bioinformatic tool that can help predict whether interspecies cross-talk between introduced and native two-component signalling pathways will occur and show both in vitro and in vivo that the predicted interactions do take place. The ability to predict potential cross-talk prior to designing and constructing novel pathways or choosing a host organism is essential for the promise that phosphosignalling components hold for synthetic biology to be realised.

Mutual information and variants for protein domain-domain contact prediction

BackgroundPredicting protein contacts solely based on sequence information remains a challenging problem, despite the huge amount of sequence data at our disposal. Mutual Information (MI), an information theory measure, has been extensively employed and modified to identify residues within a protein (intra-protein) that are in contact. More recently MI and its variants have also been used in the prediction of contacts between proteins (inter-protein).MethodsHere we assess the predictive power of MI and variants for domain-domain contact prediction. We test original MI and these variants, which are called MIp, MIc and ZNMI, on 40 domain-domain test cases containing 10,753 sequences. We also propose and evaluate two new versions of MI that consider triangles of residues and the physiochemical properties of the amino acids, respectively.ResultsWe found that all versions of MI are skewed towards predicting surface residues. Since domain-domain contacts are on the surface of each domain, we considered only surface residues when attempting to predict contacts. Our analysis shows that MIc is the best current MI domain-domain contact predictor. At 20% recall MIc achieved a precision of 44.9% when only surface residues were considered. Our triangle and reduced alphabet variants of MI highlight the delicate trade-off between signal and noise in the use of MI for domain-domain contact prediction. We also examine a specific “successful” case study and demonstrate that here, when considering surface residues, even the most accurate domain-domain contact predictor, MIc, performs no better than random.ConclusionsAll tested variants of MI are skewed towards predicting surface residues. When considering surface residues only, we find MIc to be the best current MI domain-domain contact predictor. Its performance, however, is not as good as a non-MI based contact predictor, i-Patch. Additionally, the intra-protein contact prediction capabilities of MIc outperform its domain-domain contact prediction abilities.