Multicellularity drives ecological diversity in a long-term evolution experiment.

Multicellularity drives ecological diversity in a long-term evolution experiment.
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在长期进化实验中,多细胞性驱动了生态多样性。

DOI:
10.1038/s41559-024-02391-y
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发表时间:
2024
影响因子:
16.8
通讯作者:
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中科院分区:
生物学1区
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Phototrophic metabolism, the capture of light for energy, was a pivotal biological innovation that greatly increased the total energy available to the biosphere. Chlorophyll-based photosynthesis is the most familiar phototrophic metabolism, but retinal-based microbial rhodopsins transduce nearly as much light energy as chlorophyll does, 1 via a simpler mechanism, and are found in far more taxonomic groups. Although this system has apparently spread widely via horizontal gene transfer, 2–4 little is known about how rhodopsin genes (with phylogenetic origins within prokaryotes 5, 6) are horizontally acquired by eukaryotic cells with complex internal membrane architectures or the conditions under which they provide a fitness advantage. To address this knowledge gap, we sought to determine whether Saccharomyces cerevisiae, a heterotrophic yeast with no known evolutionary history of phototrophy, can function as a facultative photoheterotroph after acquiring a single rhodopsin gene. We inserted a rhodopsin gene from Ustilago maydis, 7 which encodes a proton pump localized to the vacuole, an organelle normally acidified via a V-type rotary ATPase, allowing the rhodopsin to supplement heterotrophic metabolism. Probes of the physiology of modified cells show that they can deacidify the cytoplasm using light energy, demonstrating the ability of rhodopsins to ameliorate the effects of starvation and quiescence. Further, we show that yeast-bearing rhodopsins gain a selective advantage when illuminated, proliferating more rapidly than their non-phototrophic ancestor or rhodopsin-bearing yeast cultured in the dark. These results underscore the ease with which rhodopsins may be horizontally transferred even in eukaryotes, providing novel biological function without first requiring evolutionary optimization.