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Microbial Ecology

, Volume 57, Issue 1, pp 140–150 | Cite as

Salinity and Temperature Effects on Physiological Responses of Vibrio fischeri from Diverse Ecological Niches

  • W. Soto
  • J. Gutierrez
  • M. D. Remmenga
  • M. K. Nishiguchi
Original Article

Abstract

Vibrio fischeri is a bioluminescent bacterial symbiont of sepiolid squids (Cephalopoda: Sepiolidae) and monocentrid fishes (Actinopterygii: Monocentridae). V. fischeri exhibit competitive dominance within the allopatrically distributed squid genus Euprymna, which have led to the evolution of V. fischeri host specialists. In contrast, the host genus Sepiola contains sympatric species that is thought to have given rise to V. fischeri that have evolved as host generalists. Given that these ecological lifestyles may have a direct effect upon the growth spectrum and survival limits in contrasting environments, optimal growth ranges were obtained for numerous V. fischeri isolates from both free-living and host environments. Upper and lower limits of growth were observed in sodium chloride concentrations ranging from 0.0% to 9.0%. Sepiola symbiotic isolates possessed the least variation in growth throughout the entire salinity gradient, whereas isolates from Euprymna were the least uniform at <2.0% NaCl. V. fischeri fish symbionts (CG101 and MJ101) and all free-living strains were the most dissimilar at >5.0% NaCl. Growth kinetics of symbiotic V. fischeri strains were also measured under a range of salinity and temperature combinations. Symbiotic V. fischeri ES114 and ET101 exhibited a synergistic effect for salinity and temperature, where significant differences in growth rates due to salinity existed only at low temperatures. Thus, abiotic factors such as temperature and salinity have differential effects between free-living and symbiotic strains of V. fischeri, which may alter colonization efficiency prior to infection.

Keywords

Generation Time Vibrio Initial Cell Density Vibrio Species Competitive Dominance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work was supported in part by grants from the National Science Foundation Population Biology program (DEB-0316516) and the National Institutes of Health (SO6 GM008136-32S2-1) to M.K.N. W. Soto and J. Gutierrez were both supported by the NIH-MBRS RISE program (GM-61222-01) and the Howard Hughes Medical Institute (52005881). The authors would also like to thank A. Burris and J.G. Easterling (MBRS-RISE) for additional help with this study.

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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • W. Soto
    • 1
  • J. Gutierrez
    • 1
  • M. D. Remmenga
    • 2
  • M. K. Nishiguchi
    • 1
  1. 1.Department of Biology, MSC 3AFNew Mexico State UniversityLas CrucesUSA
  2. 2.Economics/International Business and University Statistics CenterLas CrucesUSA

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