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demonstrated that Shigella groups into two clusters ( Sims and Kim, 2011 ). If the
accessory genome is included in the analysis, Shigella group into one monophy-
letic cluster ( Sims and Kim, 2011 ; Zhang and Lin, 2012 ); this is likely due to the
shared presence of pINV. Nine complete genomes are now publically available
for Shigella ( Table 2.1 ). A recent study sequenced an additional 55 genomes
available in high-quality draft status. A whole genome alignment and phylogeny
of 69 Shigella genomes demonstrated that all Shigella group into five mono-
phyletic clades that contain a mix of 'species' based on serotyping ( Sahl et al.,
2012 ). A large-scale genomic analysis of 337 E. coli / Shigella genomes demon-
strated the presence of three exclusive clusters of Shigella that contain the five
monophyletic clades. Previous studies using limited conserved gene-based data
had suggested that Shigella had evolved from E. coli multiple times, up to seven
defining events ( Ochman et al., 1983 ; Pupo et al., 2000 ), however the genomic
data indicate that there have only been three radiations from E. coli ; these three
events include the separation of the S. dysenteriae from the enterohemorrhagic
E. coli , and the separation of two other mixed Shigella species groups in phylo-
genetic group A and B1. While these findings do not follow the 'species' lines in
Shigella , they will allow clarification of the Shigella evolutionary path and the
relationship to E. coli.
Shigella are almost indistinguishable from several enteroinvasive E. coli
(EIEC), which also contain the invasion plasmid, pINV, and show signs of
genome reduction ( Pupo et al., 2000 ). Only one EIEC genome, E. coli 53638,
is available in Genbank and is frequently not included in studies of Shigella
gene content and evolution ( Pupo et al., 2000 ; Zhang and Lin, 2012 ). Additional
genomics studies are required in order to characterize the genomic content and
phylogenetic diversity of EIEC isolates.
FUTURE DIRECTIONS
Whole genome sequence analysis has revealed information on important evolu-
tionary relationships between E. coli and Shigella isolates. Comparative analyses
have also been used to identify conserved regions that will result in more accurate
and more rapid diagnostic assays. Accurate diagnostics will likely help with food
safety, as food supplies can be quickly surveyed for the presence of potential
human pathogens. In addition to diagnostics, food safety, and surveillance, whole
genome sequence data can be used to better understand outbreak events in real
time. This was showcased by the E. coli outbreak in Germany, in which a global
crowd-sourcing effort was conducted to analyze the isolate ( Rohde et al., 2011 ).
These analyses are likely to be more common as data sharing becomes more
common.
Whole genome sequence data will also be more important in the diag-
nosis of human infections. If human samples can be quickly sequenced
and the infecting pathogen accurately identified, then treatment therapies
can be more quickly applied and modified. Furthermore, understanding the
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