Two New Alginate Lyases of PL7 and PL6 Families from Polysaccharide-Degrading Bacterium Formosa algae KMM 3553T: Structure, Properties, and Products Analysis

A bifunctional alginate lyase (ALFA3) and mannuronate-specific alginate lyase (ALFA4) genes were found in the genome of polysaccharide-degrading marine bacterium Formosa algae KMM 3553^T. They were classified to PL7 and PL6 polysaccharide lyases families and expressed in E. coli. The recombinant ALFA3 appeared to be active both on mannuronate- and guluronate-enriched alginates, as well as pure sodium mannuronate. For all substrates, optimum conditions were pH 6.0 and 35 °C; Km was 0.12 ± 0.01 mg/ml, and half-inactivation time was 30 min at 42 °C. Recombinant ALFA4 was active predominately on pure sodium mannuronate, with optimum pH 8.0 and temperature 30 °C, Km was 3.01 ± 0.05 mg/ml. It was stable up to 30 °C; half-inactivation time was 1h 40 min at 37 °C. ¹H NMR analysis showed that ALFA3 degraded mannuronate and mannuronate-guluronate blocks, while ALFA4 degraded only mannuronate blocks, producing mainly disaccharides. Products of digestion of pure sodium mannuronate by ALFA3 at 200 µg/ml inhibited anchorage-independent colony formation of human melanoma cells SK-MEL-5, SK-MEL-28, and RPMI-7951 up to 17% stronger compared to native polymannuronate. This fact supports previous data and suggests that mannuronate oligosaccharides may be useful for synergic tumor therapy.

Multifractal characterization of stochastic resonance

We use a multifractal formalism to study the effect of stochastic resonance in a noisy bistable system driven by various input signals. To characterize the response of a stochastic bistable system we introduce a new measure based on the calculation of a singularity spectrum for a return time sequence. We use wavelet transform modulus maxima method for the singularity spectrum computations. It is shown that the degree of multifractality defined as a width of singularity spectrum can be successfully used as a measure of complexity both in the case of periodic and aperiodic (stochastic or chaotic) input signals. We show that in the case of periodic driving force, singularity spectrum can change its structure qualitatively becoming monofractal in the regime of stochastic synchronization. This fact allows us to consider the degree of multifractality as a new measure of stochastic synchronization also. Moreover, our calculations have shown that the effect of stochastic resonance can be catched by this measure even from a very short return time sequence. We use also the proposed approach to characterize the noise-enhanced dynamics of a coupled stochastic neurons model.