The genus Clavibacter has been associated largely with plant diseases. The aims of this study were to characterize the genomes and the virulence factors of Chilean C. michiganensis subsp. michiganensis strains VL527, MSF322 and OP3, and to define their phylogenomic positions within the species, Clavibacter michiganensis. VL527 and MSF322 genomes possess 3,396,632 and 3,399,199 bp, respectively, with a pCM2-like plasmid in strain VL527, with pCM1- and pCM2-like plasmids in strain MSF322. OP3 genome is composed of a chromosome and three plasmids (including pCM1- and pCM2-like plasmids) of 3,466,104 bp. Genomic analyses confirmed the phylogenetic relationships of the Chilean strains among C.michiganensis subsp. michiganensis and showed their low genomic diversity. Different virulence levels in tomato plants were observable. Phylogenetic analyses of the virulence factors revealed that the pelA1 gene (chp/tomA region)—that grouped Chilean strains in three distinct clusters—and proteases and hydrolases encoding genes, exclusive for each of the Chilean strains, may be involved in these observed virulence levels. Based on genomic similarity (ANIm) analyses, a proposal to combine and reclassify C. michiganensis subsp. phaseoli and subsp. chilensis at the species level, as C. phaseoli sp. nov., as well as to reclassify C. michiganensis subsp. californiensis as the species C. californiensis sp. nov. may be justified.

The integration of machine learning techniques and metaheuristic algorithms is an area of interest due to the great potential for applications. In particular, using these hybrid techniques to solve combinatorial optimization problems (COPs) to improve the quality of the solutions and convergence times is of great interest in operations research. In this article, the db-scan unsupervised learning technique is explored with the goal of using it in the binarization process of continuous swarm intelligence metaheuristic algorithms. The contribution of the db-scan operator to the binarization process is analyzed systematically through the design of random operators. Additionally, the behavior of this algorithm is studied and compared with other binarization methods based on clusters and transfer functions (TFs). To verify the results, the well-known set covering problem is addressed, and a real-world problem is solved. The results show that the integration of the db-scan technique produces consistently better results in terms of computation time and quality of the solutions when compared with TFs and random operators. Furthermore, when it is compared with other clustering techniques, we see that it achieves significantly improved convergence times.

Bacterial canker caused by Clavibacter michiganensis subsp. michiganensis (Cmm) is one of the most important bacterial diseases of tomato. In order to understand the emergence and dissemination of this pathogen in Chile, Chilean Cmm strains isolated from different sites in central Chile were characterized and compared to a worldwide collection of strains. Multilocus sequence analysis and typing (MLSA‐MLST) based on five housekeeping genes, i.e. atpD, dnaK, gyrB, ppk and recA, and multilocus variable number of tandem repeats (VNTR) analysis (MLVA) based on eight VNTRs were used. Low diversity was found using MLSA‐MLST among the 25 Chilean strains, which clustered into three groups, each corresponding to a single sequence type (ST). Group I contained most strains (21/25), isolated over different years from Valparaíso and O'Higgins regions. Group II contained only one strain from Maule region that was isolated in 2005. These two groups belonged to the same genetic lineage. Group III contained three strains from Valparaíso region isolated in 2004, 2012 and 2013. MLVA also distributed the strains into the same three groups. Group III strains shared the same ST as strains from Algeria, Belgium, France, the Netherlands, Uruguay and the USA. Group II strains shared the same ST as strains from Brazil and Uruguay, while Group I strains shared the same ST as two strains of unknown origin. This study shows that Cmm strains from central Chile tend to be clonal and have similar genetic profiles to strains from other countries.

Cold stress decreases the growth and productivity of agricultural crops. Psychrotolerant plant growth-promoting bacteria (PGPB) may protect and promote plant growth at low temperatures. The aims of this study were to isolate and characterize psychrotolerant PGPB from wild flora of Andes Mountains and Patagonia of Chile and to formulate PGPB consortia. Psychrotolerant strains were isolated from 11 wild plants (rhizosphere and phyllosphere) during winter of 2015. For the first time, bacteria associated with Calycera, Orites, and Chusquea plant genera were reported. More than 50% of the 130 isolates showed ≥33% bacterial cell survival at temperatures below zero. Seventy strains of Pseudomonas, Curtobacterium, Janthinobacterium, Stenotrophomonas, Serratia, Brevundimonas, Xanthomonas, Frondihabitans, Arthrobacter, Pseudarthrobacter, Paenarthrobacter, Brachybacterium, Clavibacter, Sporosarcina, Bacillus, Solibacillus, Flavobacterium, and Pedobacter genera were identified by 16S rRNA gene sequence analyses. Ten strains were selected based on psychrotolerance, auxin production, phosphate solubilization, presence of nifH (nitrogenase reductase) and acdS (1-aminocyclopropane-1-carboxylate (ACC) deaminase) genes, and anti-phytopathogenic activities. Two of the three bacterial consortia formulated promoted tomato plant growth under normal and cold stress conditions. The bacterial consortium composed of Pseudomonas sp. TmR5a & Curtobacterium sp. BmP22c that possesses ACC deaminase and ice recrystallization inhibition activities is a promising candidate for future cold stress studies.