This study is reported by the research group led by Lei Zhou and Xiaoyong Zhang from the South China Agricultural University, Guangzhou. While host-specific microbial communities are common across the animal kingdom, the relative importance of host phylogeny (evolutionary history) versus functional traits in shaping these communities has remained a subject of intense debate. By examining the gut microbiota of 61 sympatric fish species within the ecologically diverse Pearl River Estuary, the research team utilized this "natural laboratory" to disentangle complex biological drivers without the interference of geographical variation.
The team discovered a surprisingly weak phylogenetic signal in the gut microbiota, meaning that more closely related fish species do not necessarily harbor more similar microbial communities. Instead, significant correlations were found between microbiota structure and the fishes' ecological guild, habitat, feeding strategies, and trophic levels. Specifically, functional traits such as eye size, oral gape shape, and gut length emerged as the primary mediators of microbiota differentiation. Using machine learning and clustering analyses, the researchers identified three distinct enterotypes among the estuarine fish. These microbial clusters are strongly associated with dietary habits and migratory behaviors, uncovering specific metabolic adaptations, such as nutrient utilization and stress resistance, tailored to the host's lifestyle.
Based on these findings, the authors proposed the concept of "Functsymbiosis." This term defines the evolutionary and ecological consistency between a host’s functional traits and its symbiotic microbiota, suggesting that the "holobiont" (the host and its microbes) adapts to environmental niches primarily through functional selection. This work provides new insights into how diverse fish species maintain their fitness and niche differentiation in complex estuarine ecosystems.
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Functional traits shape gut microbial assembly beyond phylogeny in estuarine fish.
Science China Life Sciences