Historical data suggests that prolonged survival of Brucella vaccine organisms in
the target host enhances immune protection. Recent research has focused upon the
development of rough vaccine strains to avoid interference with standard diagnostic
tests. Rough organisms are rapidly cleared from the host, however. In an effort to
develop improved vaccine strains, we have screened signature tagged mutagenesis banks
to identify mutants with varying survival characteristics. We hypothesize that in order
for a vaccine to be efficacious, it must survive in the host. In order to test this, we
constructed marked and unmarked deletion mutants of B. abortus and B. melitensis in
genes previously demonstrated by transposon mutagenesis to attenuate in vivo and in
vitro virulence. Survival and efficacy of these novel deletion mutants were then
evaluated in the mouse model. The asp24 mutants, which persist for extended periods in
vivo, appear superior as a vaccine candidate compared to approved vaccine strains S19
and Rev1 in the mouse model against either homologous or heterologous challenges.
Once enhanced protection against infection was demonstrated in the mouse, components
of immune function that appeared to be most important were identified to correlate the
immune response with the observed protection. We demonstrated that the most persistent mutant, delta-asp24, affords the greatest protection in mice against virulent
challenge. In order to evaluate safety of the novel vaccine strains as well as protection
against infection and abortion, we tested selected B. melitensis unmarked deletion
mutants in a natural host, the goat. The delta-asp24 mutant was shown to be safe in pregnant
goats while providing significant protection against infection and abortion.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/4197 |
| Date | 30 October 2006 |
| Creators | Kahl, Melissa Marie |
| Contributors | Ficht, Thomas A. |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Electronic Dissertation, text |
| Format | 11457616 bytes, electronic, application/pdf, born digital |
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