RsmC and FlhDC are global regulators controlling extracellular proteins/enzymes, rsmB RNA, motility, and virulence of Erwinia carotovora subsp. carotovora. FlhDC, the master regulator of flagellar genes, controls these traits by positively regulating gacA, fliA, and rsmC and negatively regulating hexA. RsmC, on the other hand, is a negative regulator of extracellular proteins/enzymes, motility, and virulence since the deficiency of RsmC in FlhDC(+) strain results in overproduction of extracellular proteins/enzymes, hypermotility, and hypervirulence. These phenotypes are abolished in an RsmC(-) FlhDC(-) double mutant. We show that RsmC interferes with FlhDC action. Indeed, the expression of all three targets (i.e., gacA, rsmC, and fliA) positively regulated in E. carotovora subsp. carotovora by FlhDC is inhibited by RsmC. RsmC also partly relieves the inhibition of hexA expression by FlhDC. The results of yeast two-hybrid analysis revealed that RsmC binds FlhD and FlhDC, but not FlhC. We propose that binding of RsmC with FlhD/FlhDC interferes with its regulatory functions and that RsmC acts as an anti-FlhD(4)FlhC(2) factor. We document here for the first time that RsmC interferes with activation of fliA and motility in several members of the Enterobacteriaceae family. The extent of E. carotovora subsp. carotovora RsmC-mediated inhibition of FlhDC-dependent expression of fliA and motility varies depending upon enterobacterial species. The data presented here support the idea that differences in structural features in enterobacterial FlhD are responsible for differential susceptibility to E. carotovora subsp. carotovora RsmC action.
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http://dx.doi.org/10.1128/JB.00154-09 | DOI Listing |
Heliyon
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Department of Land, Environment, Agriculture and Forestry (TESAF), University of Padova, 35020 Legnaro, Italy.
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Department of Chemistry, National Chung Hsing University, Taichung City 400, Taiwan.
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Faculty of Agro-Based Industry, Universiti Malaysia Kelantan, Jeli 17600, Malaysia.
The present study aims to characterize and predict models for antibacterial activity of a novel oligosaccharide from against subsp. using an adaptive neuro-fuzzy inference system and an artificial neural network. The mathematical predication models were used to determine the optimal conditions to produce oligosaccharide and determine the relationship between the factors (pH, temperature, and time).
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