Metapopulation structure of Vibrionaceae among coastal marine invertebrates.
Although animal-associated microbial communities (microbiomes) are increasingly recognized to influence health, the extent to which animals represent highly selective habitats for microbes leading to predominance of high host specificity remains poorly understood. Here, we show that vibrios, which are well-known commensals and opportunistic pathogens of marine animals, overall display little host preference, likely because of efficient dispersal-colonization dynamics mediated by food items. We isolated 1753 strains from water and animal samples, which are linked in a food chain and display different degrees of similarity (respiratory and digestive tract of mussels and crabs, live and dead zooplankton, and whole water samples). Multilocus sequence data served as input for modelling and statistical analysis of spatiotemporal population structure. These data showed that the majority of populations occurred broadly within and among hosts, with the dominant population being a near perfect generalist with regard to seasons, host taxa and body regions. Zooplankton harboured the fewest and most specific populations, while crabs and mussels contained the highest diversity with little evidence for host preferences. Most mussel- and crab-associated populations were detected in water samples at similar frequencies, particularly in filter-feeding mussels where populations were also evenly distributed across host individuals. The higher variation among individuals observed in crabs and zooplankton is consistent with stochastic clonal expansions. These patterns suggest that evolution of a high degree of host specificity is surprisingly rare even though these animals represent long-lived habitats, and vibrios are consistent members of their microbiome. Instead, many of the populations show stronger association with planktonic (micro)habitats while the microbiome may be a fairly open system for vibrios in which high rates of immigration can outpace selection for specialization.
Preheim
Sarah P
SP
Departments of Civil and Environmental EngineeringBiological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
Boucher
Yan
Y
Departments of Civil and Environmental EngineeringBiological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
Wildschutte
Hans
H
Departments of Civil and Environmental EngineeringBiological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
David
Lawrence A
LA
Departments of Civil and Environmental EngineeringBiological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
Veneziano
Daniele
D
Departments of Civil and Environmental EngineeringBiological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
Alm
Eric J
EJ
Departments of Civil and Environmental EngineeringBiological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
Polz
Martin F
MF
Departments of Civil and Environmental EngineeringBiological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
D000818:Animals; D058507:Host Specificity; D007448:Invertebrates / Q000382:microbiology*; D058885:Multilocus Sequence Typing; D010802:Phylogeny; D012621:Seasons; D012623:Seawater / Q000382:microbiology; D014737:Vibrionaceae / Q000145:classification* / Q000235:genetics / Q000302:isolation & purification; D014871:Water Microbiology