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Browsing by Author "Mackey, David"

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    Application of alignment-free bioinformatics methods to identify an oomycete protein with structural and functional similarity to the bacterial AvrE effector protein
    Deb, Devdutta; Mackey, David; Opiyo, Stephen O.; McDowell, John M. (PLOS, 2018-04-11)
    Diverse plant pathogens export effector proteins to reprogram host cells. One of the most challenging goals in the molecular plant-microbe field is to functionally characterize the complex repertoires of effectors secreted by these pathogens. For bacterial pathogens, the predominant class of effectors is delivered to host cells by Type III secretion. For oomycetes, the predominant class of effectors is defined by a signal peptide that mediates secretion from the oomycete and a conserved RxLR motif. Downy mildew pathogens and Phytophthora species maintain hundreds of candidate RxLR effector genes in their genomes. Although no primary sequence similarity is evident between bacterial Type III effectors (T3Es) and oomycete RXLR effectors, some bacterial and oomycete effectors have convergently evolved to target the same host proteins. Such effectors might have evolved domains that are functionally similar but sequence-unrelated. We reasoned that alignment-free bioinformatics approaches could be useful to identify structural similarities between bacterial and oomycete effectors. To test this approach, we used partial least squares regression, alignment-free bioinformatics methods to identify effector proteins from the genome of the oomycete Hyaloperonospora arabidopsidis that are similar to the well-studied AvrE1 effector from Pseudomonas syringae. This approach identified five RxLR proteins with putative structural similarity to AvrE1. We focused on one, HaRxL23, because it is an experimentally validated effector and it is conserved between distantly related oomycetes. Several experiments indicate that HaRxL23 is functionally similar to AvrE1, including the ability to partially rescue an AvrE1 loss-of-function mutant. This study provides an example of how an alignment-free bioinformatics approach can identify functionally similar effector proteins in the absence of primary sequence similarity. This approach could be useful to identify effectors that have convergently evolved regardless of whether the shared host target is known.
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    The Transcription Factor Lrp of Pantoea stewartii subsp. stewartii Controls Capsule Production, Motility, and Virulence Important for in planta Growth
    Bartholomew, Holly P.; Reynoso, Guadalupe; Thomas, Brandi J.; Mullins, Chase M.; Smith, Chastyn; Gentzel, Irene N.; Giese, Laura A.; Mackey, David; Stevens, Ann M. (Frontiers, 2022-02-14)
    The bacterial phytopathogen Pantoea stewartii subsp. stewartii causes leaf blight and Stewart's wilt disease in susceptible corn varieties. A previous RNA-Seq study examined P. stewartii gene expression patterns during late-stage infection in the xylem, and a Tn-Seq study using a P. stewartii mutant library revealed genes essential for colonization of the xylem. Based on these findings, strains with in-frame chromosomal deletions in the genes encoding seven transcription factors (NsrR, IscR, Nac, Lrp, DSJ_00125, DSJ_03645, and DSJ_18135) and one hypothetical protein (DSJ_21690) were constructed to further evaluate the role of the encoded gene products during in vitro and in planta growth. Assays for capsule production and motility indicate that Lrp plays a role in regulating these two key physiological outputs in vitro. Single infections of each deletion strain into the xylem of corn seedlings determined that Lrp plays a significant role in P. stewartii virulence. In planta xylem competition assays between co-inoculated deletion and the corresponding complementation or wild-type strains as well as in vitro growth curves determined that Lrp controls functions important for P. stewartii colonization and growth in corn plants, whereas IscR may have a more generalized impact on growth. Defining the role of essential transcription factors, such as Lrp, during in planta growth will enable modeling of key components of the P. stewartii regulatory network utilized during growth in corn plants.