Surviving in high stress environments: Physiological and molecular responses of lobe coral indicate nearshore adaptations to anthropogenic stressors

2020 
Corals in nearshore marine environments are increasingly exposed to reduced water quality, which is the primary local threat to coral reefs in Hawaii. It is unclear if corals surviving in such conditions may have acclimatized and/or adapted to withstand sedimentation, pollutants, and other environmental stressors. Lobe coral (Porites lobata) populations from Maunalua Bay, Hawaii showed clear genetic differentiation along with distinct cellular protein expression profiles between the 9polluted, high-stress9 nearshore site and the 9lower-stress9 offshore site. To understand the driving force of the observed genetic partitioning, reciprocal transplant and common-garden experiments were conducted using these nearshore and offshore coral colonies from Maunalua Bay to assess phenotypic differences of stress-related physiological and molecular responses between the two populations. Physiological responses (tissue layer thickness, tissue lipid content, and short-term growth rates) were significantly different between the populations, revealing more stress-resilient traits in the nearshore corals. Changes in protein profiles between the two populations highlighted the inherent differences in the cellular metabolic processes and activities under the same environmental conditions; nearshore corals did not significantly alter their proteome between the sites, while offshore corals responded to nearshore transplantation with increased abundances of proteins associated with detoxification, antioxidant defense, and regulation of cellular metabolic processes such as lipid oxidation. The response differences across multiple phenotypes between the two populations suggest local adaptation of nearshore corals to reduced water quality. Our results provide insight into coral9s adaptive potential and its underlying processes, and reveal potential protein biomarkers that could be used to predict resiliency.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    46
    References
    0
    Citations
    NaN
    KQI
    []