The Secreted Protease PrtA Controls Cell Growth, Biofilm Formation and Pathogenicity in Xylella fastidiosa
Hossein GouranHyrum GillespieRafael NascimentoSandeep ChakrabortyPaulo A. ZainiAaron JacobsonBrett S. PhinneyDavid DolanBlythe Durbin‐JohnsonElena S. AntonovaSteven E. LindowMatthew S. MellemaLuíz Ricardo GoulartAbhaya M. Dandekar
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Abstract Pierce’s disease (PD) is a deadly disease of grapevines caused by the Gram-negative bacterium Xylella fastidiosa . Though disease symptoms were formerly attributed to bacteria blocking the plant xylem, this hypothesis is at best overly simplistic. Recently, we used a proteomic approach to characterize the secretome of X. fastidiosa, both in vitro and in planta and identified LesA as one of the pathogenicity factors of X. fastidiosa in grapevines that leads to leaf scorching and chlorosis. Herein, we characterize another such factor encoded by PD0956, designated as an antivirulence secreted protease “PrtA” that displays a central role in controlling in vitro cell proliferation, length, motility, biofilm formation and in planta virulence. The mutant in X. fastidiosa exhibited reduced cell length, hypermotility (and subsequent lack of biofilm formation) and hypervirulence in grapevines. These findings are supported by transcriptomic and proteomic analyses with corresponding plant infection data. Of particular interest, is the hypervirulent response in grapevines observed when X. fastidiosa is disrupted for production of PrtA and that PD-model tobacco plants transformed to express PrtA exhibited decreased symptoms after infection by X. fastidiosa .Keywords:
Xylella fastidiosa
Virulence factor
Pseudomonas aeruginosa can produce a variety of virulence factors, which is one of the important reasons of chronic persistent bacteria infection. The quorum-sensing system of Pseudomonas aeruginosa is closely related to synthesis of virulence factors. In recent years, numerous studies have found that the virulence factors secreted can influence the host immune system, result in pathogenicity. So this review focuses on the related researches about pathogenicity of virulence factors.
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Pseudomonas aeruginosa; Quorum-sensing system; Virulence factor
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Cell-cell signaling in Xylella fastidiosa has been implicated in the coordination of traits enabling colonization in plant hosts as well as insect vectors. This cell density-dependent signaling has been attributed to a diffusible signaling factor (DSF) produced by the DSF synthase RpfF. DSF produced by related bacterial species are unsaturated fatty acids, but that of X. fastidiosa was thought to be different from those of other taxa. We describe here the isolation and characterization of an X. fastidiosa DSF (XfDSF) as 2(Z)-tetradecenoic acid. This compound was isolated both from recombinant Erwinia herbicola expressing X. fastidiosa rpfF and from an X. fastidiosa rpfC deletion mutant that overproduces DSF. Since an rpfF mutant is impaired in biofilm formation and underexpresses the hemagglutinin-like protein-encoding genes hxfA and hxfB, we demonstrate that these traits can be restored by ca. 0.5 µM XfDSF but not by myristic acid, the fully saturated tetradecenoic acid. A phoA-based X. fastidiosa biosensor that assesses DSF-dependent expression of hxfA or hxfB revealed a high level of molecular specificity of DSF signaling.X. fastidiosa causes diseases in many important plants, including grape, where it incites Pierce's disease. Virulence of X. fastidiosa for grape is coordinated by cell-cell signaling molecules, designated DSF (Diffusible Signaling Factor). Mutants blocked in DSF production are hypervirulent for grape, suggesting that virulence is suppressed upon DSF accumulation and that disease could be controlled by artificial elevation of the DSF level in plants. In this work, we describe the isolation of the DSF produced by X. fastidiosa and the verification of its biological activity as an antivirulence factor. We also have developed X. fastidiosa DSF biosensors to evaluate the specificity of cell-cell signaling to be investigated.
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Serial passage of Cryptococcus neoformans in mice increases virulence relative to the nonpassaged line. Postpassaged lines showed no difference in the expression of most known virulence factors, with the exception that the more virulent lines had smaller capsules in vitro. These data imply that other mechanisms of virulence remain to be discovered.
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Despite being a time when genomics and proteomics are becoming popular modes of scientific inquiry, most microbe-centric researchers continue to use reductionism to study virulence by identifying the microbial characteristics associated with virulence and characterizing each independently. Reductionism is a critical and remarkably powerful tool for determining the contribution of a single virulence factor to the overall virulence phenotype. However, the approach has the following limitation: most pathogenic microbes possess numerous attributes that contribute to virulence, and this virulence is a microbial trait that is expressed only in a susceptible host. Unfortunately, it is often very difficult, if not impossible with current technology, to study combinations of virulence factors simultaneously, especially at the molecular level. Hence, new tools are needed to study the larger picture of virulence in a pathogenic organism and to better understand how the host and microbe interact. And while computer modeling, genomics, and proteomics contribute much to the larger picture of virulence, a more accessible method is available via multivariate statistics. Consider two microbes: Cryptococcus neoformans and Bacillus anthracis. For C. neoformans, at least a half-dozen cellular attributes have been associated with virulence, including the polysaccharide capsule, melanin production, phospholipase secretion, mating factor, laccase, and urease [1]. Similarly, for B. anthracis the poly-D-glutamic acid capsule, lethal toxin, edema factor, and anthrolysin are each associated with the virulence phenotype [2,3]. Since immune responses to virulence factors often negate the virulence phenotype, vaccines often target virulence factors, as is the case for both C. neoformans and B. anthracis. In addition, the highly successful vaccines to Streptococcus pneumoniae and Haemophilus influenzae type B elicit antibodies to their polysaccharide capsules. In the same way, toxoid vaccines protect against tetanus and diphtheria by eliciting neutralizing antibody responses. Consequently, an investigator may want to prioritize the relative importance of virulence factors that contribute to the overall virulence phenotype, especially when designing new vaccines or antimicrobial drugs. However, to our knowledge, no methods have been developed to accomplish this. Fortunately, the goal of prioritizing virulence factors for an individual microbe is similar to problems that have been encountered and solved in other disciplines where investigators have had to confront phenomena caused by multiple components. Sophisticated statistical methods have been developed to approach these problems and are applicable to the problem of microbial virulence. A commonly used statistical tool is multivariate linear regression analysis (MLRA), which has found a myriad of uses in the social sciences, biology, and medicine. For example, MLRA has been used to study aspects of school readiness such as the prediction of learning-related skills in children [4], factors that contribute to smoking in youths [5], the degree and location of white matter changes in patients with Alzheimer disease [6], and whether hand lead contamination is associated with blood lead contamination [7]. MLRA simultaneously assesses the relationships of many independent variables to one dependent variable, and can easily be used to examine the relative contribution of microbial virulence factors to virulence. In fact, MLRA can be used to rank virulence factors in disease importance. There are three different kinds of MLRA: standard multiple regression, sequential (hierarchical) regression, and statistical regression [8]. In standard multiple regression, all independent variables are entered together so that the relative contribution of each independent variable to the dependent variable is assessed at the same time. Thus, standard regression illustrates how much of the dependent variable is explained by each of the independent variables at once. In hierarchical regression, the independent variables are entered in different steps in a specific order, with the order of entry resulting from theoretical or logical importance. Thus, hierarchical regression allows the investigator to examine the unique contribution of each independent predictor variable to the variance in the dependent variable, while taking into account the contribution of previously identified independent variables. In statistical regression, the independent variables are entered or removed in different steps, in an order that is specified by statistical criteria. Thus, statistical regression is useful for selecting which independent variables best predict the dependent variable when there is no theoretical rationale for a priori prioritization [8]. Depending on how much information is available on certain microbial virulence factors, and the focus of the research question, investigators can use any or all of the different kinds of MLRA. One limitation of MLRA is the need for an adequate sample size. A general rule of thumb is that ten data points
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The virulence factor concept has been a powerful engine in driving research and the intellectual flow in the fields of microbial pathogenesis and infectious diseases. This review analyzes virulence factors from the viewpoint of the damage–response framework of microbial pathogenesis, which defines virulence factor as microbial components that can damage a susceptible host. At a practical level, the finding that effective immune responses often target virulence factors provides a roadmap for future vaccine design. However, there are significant limitations to this concept, which are rooted in the inability to define virulence and virulence factors in the absence of host factors and the host response. In fact, this concept appears to work best for certain types of bacterial pathogens, being less well suited for viruses and commensal organisms with pathogenic potential.
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Abstract Given the rise of bacterial resistance against antibiotics, we urgently need alternative strategies to fight infections. Some propose we should disarm rather than kill bacteria, through targeted disruption of their virulence factors. It is assumed that this approach (i) induces weak selection for resistance because it should only minimally impact bacterial fitness, and (ii) is specific, only interfering with the virulence factor in question. Given that pathogenicity emerges from complex interactions between pathogens, hosts, and their environment, such assumptions may be unrealistic. To address this issue in a test case, we conducted experiments with the opportunistic human pathogen Pseudomonas aeruginosa , where we manipulated the availability of a virulence factor, the iron-scavenging pyoverdine, within the insect host Galleria mellonella . We observed that pyoverdine availability was not stringently predictive of virulence, and affected bacterial fitness in non-linear ways. We show that this complexity could partly arise because pyoverdine availability affects host responses and alters the expression of regulatorily linked virulence factors. Our results reveal that virulence-factor manipulation feeds back on pathogen and host behavior, which in turn affects virulence. Our findings highlight that realizing effective and evolutionarily robust anti-virulence therapies will ultimately require deeper engagement with the intrinsic complexity of host-pathogen systems.
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