Proteome-informed interrogation of a methanogenic archaeon links stress response mechanisms with microbial performance and robustness during biomethanation.

Hydrogenotrophic methanogens are promising biocatalysts for biomethanation and carbon dioxide utilization, yet their robustness under bioprocess perturbations remains insufficiently defined. We quantified robustness in a Methanothermobacter archaeal strain with proven potential for industrial application across temperature shifts, oxidative exposure, nitrogen depletion, and hydrogen starvation, measured five key cellular functions in batch culture, and derived a Fano factor based robustness metric that links data dispersion to functional stability. Thermal and oxidative stress were the primary constraints on robustness, most notably for methane productivity and lag phase duration, whereas hydrogen starvation increased productivity in some cases without large losses in robustness, and nitrogen depletion had limited effects. Global proteomics revealed coordinated changes consistent with these patterns, including increased ribosomal proteins, trehalose synthesis, chaperones, and redox regulators under thermal stress, and enrichment of PAS and histidine kinase domain proteins under oxidative stress. Structure-guided predictions using Alpha Fold 3 supported the hypothesis that stress responsive proteins may associate with canonical methanogenesis core subunits, as FmdE was predicted to associate with FmdE-like paralogs under thermal stress, while several Mtr subunits decreased in abundance. The combined results identify actionable targets for engineering robustness in methanogenic archaea, including stabilizing multi subunit methanogenesis complexes such as Mtr, tuning PAS and HK sensors to improve redox response, and modulating chaperone and osmoprotection capacity to regulate metabolic functions during temperature fluctuations. As derived future work, mapping protein interactions with abundance profiling may help move proteomics from description to prediction, providing network-informed design rules that complement conventional genome-centered proteomics and guide strain optimization of robust archaeal biocatalysts for biomethanation.