AI Article Synopsis

  • Ocean warming and acidification may affect diatoms like Pseudo-nitzschia multiseries, but the long-term impacts are not well understood.
  • The study explored how this diatom responds to changes in temperature and CO2 over at least 251 generations, finding that higher temperatures reduced growth while increased CO2 levels promoted it.
  • Results indicated that temperature is the primary factor affecting the diatom's responses, and long-term acclimation led to notable adjustments in gene expression related to stress and cellular management, suggesting that short-term experiments can help predict long-term outcomes.

Article Abstract

Ocean warming (OW) and acidification (OA) are expected to interactively impact key phytoplankton groups such as diatoms, but the underlying mechanisms, particularly under long-term acclimation, remain poorly understood. In this study, we investigated the responses of the toxic diatom Pseudo-nitzschia multiseries to combined changes in temperature (20 °C and 30 °C) and CO concentration (pCO 400 μatm and 1000 μatm) using a multi-omics approach over an acclimation period of at least 251 generations. Physiological data suggest that elevated temperature, either alone or in combination with CO, reduced the net photosynthesis and nitrate uptake rate, thus inhibiting P. multiseries growth. Conversely, elevated CO alone stimulated P. multiseries growth. Comparative genome analysis revealed the phenotypic plasticity in response to temperature and pCO variations, even after more than 251 generations acclimation period. Temperature was identified as the dominant environmental factor, showing stronger effects than CO. Transcriptomic profiles indicated that genes involved in stress- and intracellular homeostasis such as Hsps, ubiquitination process and antioxidant defense were mostly down-regulated under long-term warming acclimation. This study demonstrates that P.multiseries responds similarly to both short-term and long-term experimental selection, suggesting that short-term experiments can be used to predict long-term responses.

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Source
http://dx.doi.org/10.1016/j.marenvres.2024.106901DOI Listing

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