The members of the Bacillus thuringiensis group, commonly known as Bt, produce a huge number of metabolites, which show biocidal and antagonistic activity. B. thuringiensis is widely known for synthesizing Cry, Vip and Cyt proteins, active against insects and other parasporins with biocidal activity against certain types of cancerous cells. Nevertheless, B. thuringiensis also synthesizes compounds with antimicrobial activity, especially bacteriocins. Some B. thuringiensis bacteriocins resemble lantibiotics and other small linear peptides (class IIa) from the lactic acid bacteria bacteriocins classification system. Although many bacteriocins produced by Bt have been reported, there is no proper classification for them. In this work, we have grouped these based on molecular weight and functionality. Bacteriocins are small peptides synthesized by bacteria, presenting inhibitory activity against Gram-positive and Gram-negative bacteria and to a lesser extent against fungi. These molecules represent a good study model in the search for microbial control alternatives. Lactic acid bacteria produces a huge number of these types of molecules with great potential. Nonetheless, members of the Bacillus, cereus group, especially B. thuringiensis, emerge as an attractive alternative for obtaining bacteriocins showing novel activities. This review describes the potential applications of B. thuringiensis bacteriocins in the control of foodborne pathogens, environment and medical area.

Charolais cattle are one of the most important breeds for meat production worldwide;in México, its selection is mainly made by live weight traits. One strategy for mapping important genomic regions that might influence productive traits is the identification of signatures of selection. This type of genomic features contains loci with extended linkage disequilibrium (LD) and homozygosity patterns that are commonly associated with sites of quantitative trait locus (QTL). Therefore, the objective of this study was to identify the signatures of selection in Charolais cattle genotyped with the GeneSeek Genomic Profiler Bovine HD panel consisting of 77 K single nucleotide polymorphisms (SNPs). A total 61,311 SNPs and 819 samples were used for the analysis. Identification of signatures of selection was carried out using the integrated haplotype score (iHS) methodology implemented in the rehh R package. The top ten SNPs with the highest piHS values were located on BTA 4, 5, 6 and 14. By identifying markers in LD with top ten SNPs, the candidate regions defined were mapped to 52.8-59.3 Mb on BTA 4; 67.5-69.3 on BTA 5; 39.5-41.0 Mb on BTA 6; and 26.4-29.6 Mb on BTA 14. The comparison of these candidate regions with the bovine QTLdb effectively confirmed the association (p < 0.05) with QTL related to growth traits and other important productive traits. The genomic regions identified in this study indicated selection for growth traits on the Charolais population via the conservation of haplotypes on various chromosomes. These genomic regions and their associated genes could serve as the basis for haplotype association studies and for the identification of causal genes related to growth traits. K E Y W O R D S Charolais, integrated haplotype score, signatures of selection, single nucleotide polymorphism | 379 JAHUEY-MARTÍNEZ ET Al.

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Helicobacter pylori infects more than half of the world's population, making it the most widespread infection of bacteria. It has high genetic diversity and has been considered as one of the most variable bacterial species. In the present study, a PCR-based method was used to detect the presence and the relative frequency of homologous recombination between repeat sequences (>500 bp) in H. pylori 26695. All the recombinant structures have been confirmed by sequencing. The inversion generated between inverted repeats showed distinct features from the recombination for duplication or deletion between direct repeats. Meanwhile, we gave the mathematic reasoning of a general formula for the calculation of relative recombination frequency and indicated the conditions for its application. This formula could be extensively applied to detect the frequency of homologous recombination, site-specific recombination, and other types of predictable recombination. Our results should be helpful for better understanding the genome evolution and adaptation of bacteria.

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