RESUMO
The aim of the present work was to study the mode of the induction of the biosynthesis of macedocin, the lantibiotic produced by Streptococcus macedonicus ACA-DC 198. Macedocin was produced when the strain was grown in milk but not in MRS or M17 broth. No autoinduction mechanism was observed. Production did not depend on the presence of lactose or galactose in the culture medium or on a coculture of the producer strain with macedocin-sensitive or macedocin-resistant strains. Induction seemed to depend on the presence of one or more heat-stable protein components produced when S. macedonicus ACA-DC 198 was grown in milk. The partial purification of the induction factor was performed by a combination of chromatography methods, and its activity was confirmed by a reverse transcription-PCR approach (RT-PCR). Mass spectrometric (MS) and tandem mass spectrometric (MS/MS) analyses of an induction-active fraction showed the presence of several peptides of low molecular mass corresponding to fragments of alpha(S1)- and beta-casein as well as beta-lactoglobulin. The chemically synthesized alpha(S1)-casein fragment 37-55 (2,253.65 Da) was proven to be able to induce macedocin biosynthesis. This is the first time that milk protein degradation fragments are reported to exhibit a bacteriocin induction activity.
Assuntos
Bacteriocinas/biossíntese , Proteínas do Leite/farmacologia , Streptococcus/efeitos dos fármacos , Streptococcus/metabolismo , Sequência de Aminoácidos , Animais , Bacteriocinas/genética , Sequência de Bases , Biomarcadores Tumorais , Caseínas/química , Caseínas/genética , Caseínas/farmacologia , Meios de Cultura , Primers do DNA/genética , DNA Bacteriano/genética , Microbiologia de Alimentos , Genes Bacterianos , Técnicas In Vitro , Lactoglobulinas/química , Lactoglobulinas/genética , Lactoglobulinas/farmacologia , Proteínas do Leite/química , Proteínas do Leite/genética , Dados de Sequência Molecular , Fragmentos de Peptídeos/química , Fragmentos de Peptídeos/genética , Fragmentos de Peptídeos/farmacologia , Peptídeo Hidrolases , Streptococcus/genética , Streptococcus/crescimento & desenvolvimento , Espectrometria de Massas em TandemRESUMO
Growth of and bacteriocin production by Streptococcus macedonicus ACA-DC 198 were assessed and modeled under conditions simulating Kasseri cheese production. Controlled fermentations were performed in milk supplemented with yeast extract at different combinations of temperature (25, 40, and 55 degrees C), constant pH (pHs 5 and 6), and added NaCl (at concentrations of 0, 2, and 4%, wt/vol). The data obtained were used to construct two types of predictive models, namely, a modeling approach based on the gamma concept, as well as a model based on artificial neural networks (ANNs). The latter computational methods were used on 36 control fermentations to quantify the complex relationships between the conditions applied (temperature, pH, and NaCl) and population behavior and to calculate the associated biokinetic parameters, i.e., maximum specific growth and cell count decrease rates and specific bacteriocin production. The functions obtained were able to estimate these biokinetic parameters for four validation fermentation experiments and obtained good agreement between modeled and experimental values. Overall, these experiments show that both methods can be successfully used to unravel complex kinetic patterns within biological data of this kind and to predict population kinetics. Whereas ANNs yield a better correlation between experimental and predicted results, the gamma-concept-based model is more suitable for biological interpretation. Also, while the gamma-concept-based model has not been designed for modeling of other biokinetic parameters than the specific growth rate, ANNs are able to deal with any parameter of relevance, including specific bacteriocin production.
