Phylogenetic analysis and alignments were carried out using the Mega 4.1 software [39 (link)], but examination of resulting cladograms revealed poor resolution of clades at a subspecific level. A network of zero-step and one-step clades was therefore established using the methodology of Nested Clade Analysis and statistical parsimony [41 (link)–43 (link)] to describe the most likely mutational relationships between Bartonella isolates collected during this work. The cladogram and the limit for statistical parsimony were calculated using TCS [10 (link)]. Four isolates, EU014267, EU014269, EU014274 and EU014275, collected from the same location by Welc-Falęciak et al. [44 (link)] in 2005, were also included because they represented otherwise missing internal steps within the clade network. Log-linear models were implemented using SPSS v 14.00 to establish significant departures from randomness in the host range of isolates within each nested Bartonella clade [41 (link)]. To identify recombination within the gltA gene, the sequenced fragment was first divided into three 100 bp segments and phylogenies generated using the minimum evolution algorithm in Mega 4.1. Discrepancies between these phylogenies were then used to identify potential recombinant gltA sequences, which were analysed further to confirm or reject recombination using the RDP-2 software package [18 (link)]. To identify potential recombination events between disparate parts of the genome, isolates from the range of Bartonella gltA clades were sequenced at the other genes described. All distinct genotypes of each gene were treated as distinct alleles and coded as such. Using an MLST approach [14 (link), 29 (link)], distinct alleles were then plotted on to the cladogram and evidence was sought of disjunctions between the overall distribution of housekeeping genes and of connections between disparate clades, which could be taken as evidence of a recombinant event. The congruence of the gene phylogenies to each other and to the gltA phylogeny was tested by generating consensus (100 bootstraps) maximum likelihood phylogenies using PhyML ([20 (link)], performed on the Montpellier bioinformatics platform and the University of Oslo Bioportal), after first establishing optimal DNA evolution models for each gene using jModelTest [36 (link)]. The congruence between trees generated in this way for each gene and trees constrained by the assumption that the gltA phylogeny reflected the evolutionary history of the Bartonella isolates was tested using maximum likelihood ratio tests.
The unique sequences were deposited in GenBank under accession numbers GU338880-GU338885 (16S), GU338887-GU338901 (ftsZ), GU338903-GU338915 and GU338917-GU338924 (ribC), GU338925-GU338936 and GU338938-GU338941 (rpoB), GU338942-GU338976 (gltA), and GU559862-GU559871 and GU559873 (groEl).