Roles of Porphyromonas gulae proteases in bacterial and host cell biology

Porphyromonas gulae, an animal-derived periodontal pathogen, expresses several virulence factors, including fimbria, lipopolysaccharide (LPS) and proteases. We previously reported that its invasive efficiency was dependent on fimbriae types. In addition, P. gulae LPS increased inflammatory responses via toll-like receptors. The present study was conducted to investigate the involvement of P. gulae proteases in bacterial and host cell biology. Porphyromonas gulae strains showed an ability to agglutinate mouse erythrocytes and also demonstrated co-aggregation with Actinomyces viscosus, while the protease inhibitors antipain, PMSF, TLCK and leupeptin diminished P. gulae proteolytic activity, resulting in inhibition of haemagglutination and co-aggregation with A. viscosus. In addition, specific proteinase inhibitors were found to reduce bacterial cell growth. Porphyromonas gulae inhibited Ca9-22 cell proliferation in a multiplicity of infection- and time-dependent manner. Additionally, P. gulae-induced decreases in cell contact and adhesion-related proteins were accompanied by a marked change in cell morphology from well spread to rounded. In contrast, inhibition of protease activity prevented degradation of proteins, such as E-cadherin, beta-catenin and focal adhesion kinase, and also blocked inhibition of cell proliferation. Together, these results indicate suppression of the amount of human proteins, such as gamma-globulin, fibrinogen and fibronectin, by P. gulae proteases, suggesting that a novel protease complex contributes to bacterial virulence

Experimental investigation of performance differences between Coherent Ising Machines and a quantum annealer

Physical annealing systems provide heuristic approaches to solving NP-hard Ising optimization problems. Here, we study the performance of two types of annealing machines--a commercially available quantum annealer built by D-Wave Systems, and measurement-feedback coherent Ising machines (CIMs) based on optical parametric oscillator networks--on two classes of problems, the Sherrington-Kirkpatrick (SK) model and MAX-CUT. The D-Wave quantum annealer outperforms the CIMs on MAX-CUT on regular graphs of degree 3. On denser problems, however, we observe an exponential penalty for the quantum annealer ($\exp(-\alpha_\textrm{DW} N^2)$) relative to CIMs ($\exp(-\alpha_\textrm{CIM} N)$) for fixed anneal times, on both the SK model and on 50%-edge-density MAX-CUT, where the coefficients $\alpha_\textrm{CIM}$ and $\alpha_\textrm{DW}$ are problem-class-dependent. On instances with over $50$ vertices, a several-orders-of-magnitude time-to-solution difference exists between CIMs and the D-Wave annealer. An optimal-annealing-time analysis is also consistent with a significant projected performance difference. The difference in performance between the sparsely connected D-Wave machine and the measurement-feedback facilitated all-to-all connectivity of the CIMs provides strong experimental support for efforts to increase the connectivity of quantum annealers.Comment: 12 pages, 5 figures, 1 table (main text); 14 pages, 12 figures, 2 tables (supplementary

Scaling advantages of all-to-all connectivity in physical annealers: the Coherent Ising Machine vs. D-Wave 2000Q

Physical annealing systems provide a heuristic approach to solve NP-hard Ising optimization problems. It is believed that the connectivity between spins in such annealers significantly impacts the machine's computational effectiveness. In this paper we study the performance of two types of annealing machines that have very different connectivity -- a commercially available quantum annealer built by D-wave Systems, which has sparse connectivity, and coherent Ising machines based on optical parametric oscillator networks, which have all-to-all connectivity. We demonstrate an exponential (e^(−O(N^2))) penalty in performance for the D-wave quantum annealer relative to coherent Ising machines when solving Ising problems on dense graphs, which is attributable to the differences in internal connectivity between the machines. This leads to a several-orders-of-magnitude time-to-solution difference between coherent Ising machines and the D-wave system for problems with over 50 vertices. Our results provide strong experimental support to efforts to increase the connectivity of physical annealers

Experimental investigation of performance differences between coherent Ising machines and a quantum annealer

Physical annealing systems provide heuristic approaches to solving combinatorial optimization problems. Here, we benchmark two types of annealing machines—a quantum annealer built by D-Wave Systems and measurement-feedback coherent Ising machines (CIMs) based on optical parametric oscillators—on two problem classes, the Sherrington-Kirkpatrick (SK) model and MAX-CUT. The D-Wave quantum annealer outperforms the CIMs on MAX-CUT on cubic graphs. On denser problems, however, we observe an exponential penalty for the quantum annealer [exp(–α_(DW)N^2)] relative to CIMs [exp(–α_(CIM)N)] for fixed anneal times, both on the SK model and on 50% edge density MAX-CUT. This leads to a several orders of magnitude time-to-solution difference for instances with over 50 vertices. An optimal–annealing time analysis is also consistent with a substantial projected performance difference. The difference in performance between the sparsely connected D-Wave machine and the fully-connected CIMs provides strong experimental support for efforts to increase the connectivity of quantum annealers

Microbial Community Analysis of Field-Grown Soybeans with Different Nodulation Phenotypes▿

Microorganisms associated with the stems and roots of nonnodulated (Nod−), wild-type nodulated (Nod+), and hypernodulated (Nod++) soybeans [Glycine max (L.) Merril] were analyzed by ribosomal intergenic transcribed spacer analysis (RISA) and automated RISA (ARISA). RISA of stem samples detected no bands specific to the nodulation phenotype, whereas RISA of root samples revealed differential bands for the nodulation phenotypes. Pseudomonas fluorescens was exclusively associated with Nod+ soybean roots. Fusarium solani was stably associated with nodulated (Nod+ and Nod++) roots and less abundant in Nod− soybeans, whereas the abundance of basidiomycetes was just the opposite. The phylogenetic analyses suggested that these basidiomycetous fungi might represent a root-associated group in the Auriculariales. Principal-component analysis of the ARISA results showed that there was no clear relationship between nodulation phenotype and bacterial community structure in the stem. In contrast, both the bacterial and fungal community structures in the roots were related to nodulation phenotype. The principal-component analysis further suggested that bacterial community structure in roots could be classified into three groups according to the nodulation phenotype (Nod−, Nod+, or Nod++). The analysis of root samples indicated that the microbial community in Nod− soybeans was more similar to that in Nod++ soybeans than to that in Nod+ soybeans