Agrobacterium tumefaciens possesses two catalases, a bifunctional catalase-peroxidase, KatA and a homologue of a growth phase regulated monofunctional catalase, CatE. In stationary phase cultures and in cultures enter...
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Agrobacterium tumefaciens possesses two catalases, a bifunctional catalase-peroxidase, KatA and a homologue of a growth phase regulated monofunctional catalase, CatE. In stationary phase cultures and in cultures entering stationary phase, total catalase activity increased 2-fold while peroxidase activity declined. katA and catE were found to be independently regulated in a growth phase dependent manner. KatA levels were highest during exponential phase and declined as cells entered stationary phase, while CatE was detectable at early exponential phase and increased during stationary phase. Only small increases in H 2 O 2 resistance levels were detected as cells entering stationary phase. The katA mutant was more sensitive to H 2 O 2 than the parental strain during both exponential and stationary phase. Inactivation of catE alone did not significantly change the level of H 2 O 2 resistance. However, the katA catE double mutant was more sensitive to H 2 O 2 during both exponential and stationary phase than either of the single catalase mutants. The data indicated that KatA plays the primary role and CatE acts synergistically in protecting A. tumefaciens from H 2 O 2 toxicity during all phases of growth. Catalase-peroxidase activity (KatA) was required for full H 2 O 2 resistance. The expression patterns of the two catalases in A. tumefaciens reflect their physiological roles in the protection against H 2 O 2 toxicity, which are different from other bacteria.
This paper deals with the problem of identifying autoregressive models in presence of additive measurement noise. A new approach, based on some theoretical results concerning the so-called dynamic Frisch scheme, is pr...
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This paper deals with the problem of identifying autoregressive models in presence of additive measurement noise. A new approach, based on some theoretical results concerning the so-called dynamic Frisch scheme, is proposed. This method takes advantage of both low and high order Yule-Walker equations and allows to identify the AR parameters and the driving and output noise variances in a congruent way since the estimates assure the positive definiteness of the autocorrelation matrix of the AR process. Simulation results are reported to show the effectiveness of the proposed procedure and compare its performance with those of other identification methods.
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