Science - USA (2020-06-05)

(Antfer) #1

as a central hub connected to multiple geno-
typenodes(fig.S25).Weusethesimplecaseof
thetypeI.aTiplasmidofstrainDi1411asan
example (Fig. 6F and fig. S25F). This plasmid
has only two SNP differences relative to the
type I.a Ti plasmid of another BV2 strain. In
contrast, the two strains linked by the type I.a
Ti plasmid cluster have more than 22,000 SNP
differences in their chromosomes. The most
pronounced example has 28 BV2 strains
and one G1 strain collected from more than
20 locations that have type I.a Ti plasmids
with no more than 13 SNP differences among
them (fig. S25R and data S11). The clustering of
these29plasmidsisnotaconsequenceoflow
SNP diversity. The total of 49 type I.a Ti plas-
mids in this study formed 10 unique clusters
that vary by nearly 5000 SNP differences. The
diversity of BV2 strains is also not a conse-
quence of the conservative threshold used to
define genotypes. Even at 1000 SNP differences,
the BV2 strains would separate into 17 differ-
ent genotypes.
Management practices in agricultural ecosys-
tems have been suggested to increase opportu-
nities for plasmid conjugation ( 31 ). Supporting
evidence is found in three networks in which
the same location is mapped to a plasmid node
andmultipleassociatedgenotypenodes.Strains
of a G1 and G7 genotype carrying type III Ti
plasmids with 0 SNP differences were identi-
fied in facility S9_N46 (Fig. 6G and fig. S25G).
In the second example, one strain of a BV2
genotype and three strains of a G1 genotype
were collected from facility S2_N7 (fig. S25K).
Their type II Ti plasmids have 0 SNP differ-
ences among them. Last, a strain of a G4 geno-
type and two strains of closely related BV2
genotypeshavetypeI.aTiplasmidswith≤1SNP
difference (fig. S25S).
Plasmid dissemination can also lead to the
temporal spread and persistence of disease.
The type I.a Ti plasmid of strain K27, collected
prior to 1964, has≤2 SNP differences relative
to seven other type I.a Ti plasmids present in
strains collected during the period 1995– 2009
(Fig. 6H and fig. S25H). As previously stated,
this is likely not a reflection of low SNP di-
versity within the type I.a Ti plasmids.
We found one instance in which two closely
related strains have distantly related Ti plas-
mids, suggesting independent acquisition
events. Strain Z4/95 and strain K27 differ by
only 48 SNPs (fig. S25, L and T, and data S19).
The type I.a Ti plasmid of Z4/95 has ~2400 SNP
differences in comparison to the type I.a plas-
mid of K27 and does not cluster with any other
typeI.aTiplasmid(dataS11).


Discussion


Modularity confers phenotypic robustness
and allows oncogenic plasmids to diversify.
But diversification is opposed by selective
forces that preserve genetic and physical links


necessary to maintain functionality of the
plasmids. By accounting for variation and
constraints, we were able to sort oncogenic
plasmids into defined lineages and infer their
evolution. We revealed the most commonly
observed types, which are foundational for
understanding types yet to be discovered.
Diversification of pathogen populations by
plasmid transmission is promoted by the ag-
ricultural industry, where large populations
of susceptible host species are intensively
managed and often clonally propagated with-
in the same facilities, individuals are moved
across the world, and disease can persist un-
detected for extended periods of time. Although
clinical settings have some similar features that
promote diversification, antibiotic use is sug-
gested to result in a recurring pattern of clonal
expansion of pathogens followed by global
spread of“super-fit”bacterial lineages ( 32 ).
However, analysis of plasmids has shown that
recombination of antibiotic resistance genes
can occur, and entire plasmid sequences need
to be studied to avoid drawing misleading
conclusions ( 33 ). In addition, transmission of
plasmids can occur within and even between
genera, enhancing and promoting new epi-
demics ( 34 , 35 ). Our strategy relied on multiple
methods to determine plasmid relationships
and coupled it with ancestry of chromosomes
to unravel the mosaicism of bacterial evolu-
tion. This approach has applications to other
systems in modeling the impact of mobile ge-
netic elements on bacterial evolution to limit
risks from infectious diseases.

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