Protein Complexes in Bacteria

Large-scale analyses of protein complexes have recently become available for Escherichia coli and Mycoplasma pneumoniae, yielding 443 and 116 heteromultimeric soluble protein complexes, respectively. We have coupled the results of these mass spectrometrycharacterized protein complexes with the 285 “gold standard” protein complexes identified by EcoCyc. A comparison with databases of gene orthology, conservation, and essentiality identified proteins conserved or lost in complexes of other species. For instance, of 285 “gold standard” protein complexes in E. coli, less than 10% are fully conserved among a set of 7 distantly-related bacterial “model” species. Complex conservation follows one of three models: well-conserved complexes, complexes with a conserved core, and complexes with partial conservation but no conserved core. Expanding the comparison to 894 distinct bacterial genomes illustrates fractional conservation and the limits of co-conservation among components of protein complexes: just 14 out of 285 model protein complexes are perfectly conserved across 95% of the genomes used, yet we predict more than 180 may be partially conserved across at least half of the genomes. No clear relationship between gene essentiality and protein complex conservation is observed, as even poorly conserved complexes contain a significant number of essential proteins. Finally, we identify 183 complexes containing well-conserved components and uncharacterized proteins which will be interesting targets for future experimental studies

Multifrequency EPR Studies of [Cu^(1.5)Cu^(1.5)]+ for Cu_2(μ-NR_2)_2 and Cu_2(μ-PR_2)_2 Diamond Cores

Multifrequency electron paramagnetic resonance (EPR) spectroscopy is used to explore the electronic structures of a series of dicopper complexes of the type {(LXL)Cu}_2^+. These complexes contain two four-coordinate copper centers of highly distorted tetrahedral geometries linked by two [LXL]^− ligands featuring bridging amido or phosphido ligands and associated thioether or phosphine chelate donors. Specific chelating [LXL]^− ligands examined in this study include bis(2-tert-butylsulfanylphenyl)amide (SNS), bis(2-di-iso-butylphosphinophenyl)amide (PNP), and bis(2-di-iso-propylphosphinophenyl)phosphide (PPP). To better map the electronic coupling to copper, nitrogen, and phosphorus in these complexes, X-, S-, and Q-band EPR spectra have been obtained for each complex. The resulting EPR parameters implied by computer simulation are unusual for typical dicopper complexes and are largely consistent with previously published X-ray absorption spectroscopy and density functional theory data, where a highly covalent {Cu_2(μ-XR_2)_2}^+ diamond core has been assigned in which removal of an electron from the neutral {Cu_2(μ-XR_2)_2} can be viewed as ligand-centered to a substantial degree. To our knowledge, this is the first family of dicopper diamond core model complexes for which the compendium of X-, S-, and Q-band EPR spectra have been collected for comparison to Cu_A

Shapes of interacting RNA complexes

Shapes of interacting RNA complexes are studied using a filtration via their topological genus. A shape of an RNA complex is obtained by (iteratively) collapsing stacks and eliminating hairpin loops. This shape-projection preserves the topological core of the RNA complex and for fixed topological genus there are only finitely many such shapes.Our main result is a new bijection that relates the shapes of RNA complexes with shapes of RNA structures.This allows to compute the shape polynomial of RNA complexes via the shape polynomial of RNA structures. We furthermore present a linear time uniform sampling algorithm for shapes of RNA complexes of fixed topological genus.Comment: 38 pages 24 figure

<i>Plasmodium </i>Condensin Core Subunits SMC2/SMC4 Mediate Atypical Mitosis and Are Essential for Parasite Proliferation and Transmission

Condensin is a multi-subunit protein complex regulating chromosome condensation and segregation during cell division. In Plasmodium spp., the causative agent of malaria, cell division is atypical and the role of condensin is unclear. Here we examine the role of SMC2 and SMC4, the core subunits of condensin, during endomitosis in schizogony and endoreduplication in male gametogenesis. During early schizogony, SMC2/SMC4 localize to a distinct focus, identified as the centromeres by NDC80 fluorescence and chromatin immunoprecipitation sequencing (ChIP-seq) analyses, but do not form condensin I or II complexes. In mature schizonts and during male gametogenesis, there is a diffuse SMC2/SMC4 distribution on chromosomes and in the nucleus, and both condensin I and condensin II complexes form at these stages. Knockdown of smc2 and smc4 gene expression reveals essential roles in parasite proliferation and transmission. The condensin core subunits (SMC2/SMC4) form different complexes and may have distinct functions at various stages of the parasite life cycle

RECONSTITUTION OF ALLOPHYCOCYANIN FROM Mastigocladus laminosus WITH ISOLATED LINKER POLYPEPTIDE

The core linker polypeptide Lc 8.9 was isolated from Mastigocladus laminosus and purified on a preparative scale. A method for the reconstitution of allophycocyanin (AP)—linker complexes from isolated polypeptides was developed. The complex (αAP(βAP)3 Lc 8.9 was reconstituted and compared to (αAPβAP) and (αAPβAP)3 by sucrose density gradient ultracentrifugation, absorption, fluorescence emission and circular dichroism spectroscopy. Differences in the spectra of reconstituted and of directly isolated AP complexes are discussed

MCL-CAw: A refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure

Abstract Background The reconstruction of protein complexes from the physical interactome of organisms serves as a building block towards understanding the higher level organization of the cell. Over the past few years, several independent high-throughput experiments have helped to catalogue enormous amount of physical protein interaction data from organisms such as yeast. However, these individual datasets show lack of correlation with each other and also contain substantial number of false positives (noise). Over these years, several affinity scoring schemes have also been devised to improve the qualities of these datasets. Therefore, the challenge now is to detect meaningful as well as novel complexes from protein interaction (PPI) networks derived by combining datasets from multiple sources and by making use of these affinity scoring schemes. In the attempt towards tackling this challenge, the Markov Clustering algorithm (MCL) has proved to be a popular and reasonably successful method, mainly due to its scalability, robustness, and ability to work on scored (weighted) networks. However, MCL produces many noisy clusters, which either do not match known complexes or have additional proteins that reduce the accuracies of correctly predicted complexes. Results Inspired by recent experimental observations by Gavin and colleagues on the modularity structure in yeast complexes and the distinctive properties of "core" and "attachment" proteins, we develop a core-attachment based refinement method coupled to MCL for reconstruction of yeast complexes from scored (weighted) PPI networks. We combine physical interactions from two recent "pull-down" experiments to generate an unscored PPI network. We then score this network using available affinity scoring schemes to generate multiple scored PPI networks. The evaluation of our method (called MCL-CAw) on these networks shows that: (i) MCL-CAw derives larger number of yeast complexes and with better accuracies than MCL, particularly in the presence of natural noise; (ii) Affinity scoring can effectively reduce the impact of noise on MCL-CAw and thereby improve the quality (precision and recall) of its predicted complexes; (iii) MCL-CAw responds well to most available scoring schemes. We discuss several instances where MCL-CAw was successful in deriving meaningful complexes, and where it missed a few proteins or whole complexes due to affinity scoring of the networks. We compare MCL-CAw with several recent complex detection algorithms on unscored and scored networks, and assess the relative performance of the algorithms on these networks. Further, we study the impact of augmenting physical datasets with computationally inferred interactions for complex detection. Finally, we analyse the essentiality of proteins within predicted complexes to understand a possible correlation between protein essentiality and their ability to form complexes. Conclusions We demonstrate that core-attachment based refinement in MCL-CAw improves the predictions of MCL on yeast PPI networks. We show that affinity scoring improves the performance of MCL-CAw.http://deepblue.lib.umich.edu/bitstream/2027.42/78256/1/1471-2105-11-504.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/2/1471-2105-11-504-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/3/1471-2105-11-504-S2.ZIPhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/4/1471-2105-11-504.pdfPeer Reviewe