Authors
Sanbao Zhang, Qinyang Jiang, Junjie Ma, Jianwei Zou, Fan Wang, Feifei Lv, Yanna Huang, Yongcheng Wang, Ziye Xu
Published in
Advanced science (Weinheim, Baden-Wurttemberg, Germany). Pages e76152. Jun 15, 2026. Epub Jun 15, 2026.
Abstract
The adaptation of complex, host-associated microbiomes to environmental perturbations is a critical determinant of ecosystem stability and resilience to climate change, as exemplified in ruminants. While single-microbe RNA sequencing advances community interrogation, complex microbial cell walls severely constrain unbiased single-cell transcriptomic profiling in the rumen. In this study, we developed an optimized 25 min time-resolved enzymatic lysis strategy using smRandom-seq to map the sheep rumen microbiome at single-cell resolution. By profiling 60 748 cells across 21 samples, we captured previously intractable lineages, resolving the transcriptional states of 213 genera and 662 species, achieving a physiologically relevant 0.303% recovery of methanogenic archaea. Unsupervised clustering partitioned the ecosystem into seven cross-species functional clusters, uncovering a spatial coupling between microbial lifestyle and metabolic specialization. Applying this framework to a model of host thermal adaptation demonstrated that host resilience was associated with rapid transcriptional activation of key energy-metabolism clusters. Notably, a lineage-specific metabolic shift toward a glycolytic phenotype in Anaerovibrio lipolyticus contributes to a compensatory "nutritional sparing" effect associated with host resilience. This dataset provides a foundational resource for rumen microbial ecology and establishes a technical framework for dissecting phenotypic plasticity within complex microbiomes.
PMID:
42295802
Bibliographic data and abstract were imported from PubMed on 15 Jun 2026.
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