Abstract
Global environmental change affects organisms, including their physiology. In freshwater ecosystems, where migration is limited, populations often rely on phenotypic plasticity to respond. While transcriptomics has been widely used to study stress responses at the molecular level, less is known about the proteome, which reflects post-transcriptional and post-translational regulation that shapes the resulting phenotype. We conducted the first proteome-level study on the endangered Mira chub, Squalius torgalensis, which inhabits unstable habitats, enduring harsh summers with high temperatures and frequent droughts. We assessed the effect of warming and acidification, independently and combined, on protein expression and phosphorylation in gills and muscle using tandem mass tags labelling proteomics. While both tissues exhibited similar numbers of differentially expressed proteins, the muscle showed more differentially phosphorylated proteins, particularly under warming. We observed four protein differential expression patterns: consistent regulation across all scenarios, opposite response in one scenario, stress prioritisation in response to dominant stressor (warming), and reduced expression in combined compared to single stressors. The latter suggests a buffering mechanism that limits protein-level changes under simultaneous stressors, possibly as an energy-saving mechanism or a consequence of stress overload. A gene set enrichment-like analysis revealed that, despite the presence of distinct regulatory patterns in each tissue and condition, key biological functions like metabolism, gene/protein expression, and immunity were affected by all stressors. Gene/protein expression was the most affected at the phosphoproteome level. Our findings highlight the importance of proteomics and phosphoproteomics studies to understand species' molecular responses to climate change. By identifying key proteins involved in resilience, we pinpointed candidate stress markers for the Mira chub that can be used to assess the impact of environmental changes. Integrating these tools with genomics and ecological modelling could help improve predictive models for climate adaptation and species conservation.