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Friend or Foe: Symbiotic Bacteria in Bactrocera dorsalis -Parasitoid Associations.

Rehemah GwokyalyaChristopher W WeldonJeremy Keith HerrenJoseph GichuhiEdward Edmond MakhuluShepard NdlelaSamira Abuelgasim Mohamed
Published in: Biology (2023)
Parasitoids are promising biocontrol agents of the devastating fruit fly, Bactrocera dorsalis . However, parasitoid performance is a function of several factors, including host-associated symbiotic bacteria. Providencia alcalifaciens , Citrobacter freundii , and Lactococcus lactis are among the symbiotic bacteria commonly associated with B. dorsalis , and they influence the eco-physiological functioning of this pest. However, whether these bacteria influence the interaction between this pest and its parasitoids is unknown. This study sought to elucidate the nature of the interaction of the parasitoids, Fopius arisanus , Diachasmimorpha longicaudata , and Psyttlia cosyrae with B. dorsalis as mediated by symbiotic bacteria. Three types of fly lines were used: axenic, symbiotic, and bacteria-mono-associated ( Lactococcus lactis , Providencia alcalifaciens , and Citrobacter freundii ). The suitable stages of each fly line were exposed to the respective parasitoid species and reared until the emergence of adult flies/parasitoids. Thereafter, data on the emergence and parasitoid fitness traits were recorded. No wasps emerged from the fly lines exposed to P. cosyrae . The highest emergence of F . arisanus and D. longicaudata was recorded in the L. lactis fly lines. The parasitoid progeny from the L. lactis and P. alcalifaciens fly lines had the longest developmental time and the largest body size. Conversely, parasitoid fecundity was significantly lower in the L. lactis lines, whereas the P. alcalifaciens lines significantly improved fecundity. These results elucidate some effects of bacterial symbionts on host-parasitoid interactions and their potential in enhancing parasitoid-oriented management strategies against B. dorsalis .
Keyphrases
  • drosophila melanogaster
  • physical activity
  • body composition
  • electronic health record
  • risk assessment
  • machine learning
  • dna methylation
  • genome wide
  • young adults
  • deep learning
  • human health
  • plant growth