Tetracycline antibiotics frequently co-occur with manganese (Mn) in freshwater environments, yet how Mn background gradients reshape mixture phytotoxicity remains insufficiently resolved. The objective of this study was to systematically investigate how varying Mn background levels modulate the phytotoxicity and interaction patterns of tetracycline antibiotics. Using Lemna minor as a model species, we employed full-factorial Mn × tetracycline concentration matrices (tetracycline, TC; oxytetracycline, OTC; and chlortetracycline, CTC) to quantify Mn-dependent modulation of tetracycline toxicity and identified operational Mn regimes supported by breakpoint robustness analysis. Growth-rate responses delineated a low-Mn window (0.10–0.40 mg·L⁻¹), a transition interval (0.40–1.60 mg·L⁻¹), and a high-Mn domain (≥1.60 mg·L⁻¹). Under low Mn conditions, Mn generally promoted antagonistic interactions, with inhibition weaker than expected, a pattern consistently observed across growth, pigment, and antioxidant endpoints. In contrast, under high Mn conditions, synergistic interactions emerged at specific Mn × antibiotic combinations, characterized by stronger-than-expected inhibition, forming spatially heterogeneous interaction “islands” on the response surfaces. These regime-dependent patterns were concordant between integrated multi-endpoint ΔBliss interaction landscapes, which quantify deviations from Bliss independence, and potency-surface validation using δZIP, a zero-interaction potency (ZIP)–based deviation metric, based on chlorophyll a. Overall, the results support a threshold-based, operational reporting framework linking Mn regimes to mixture interaction landscapes and indicate that mixture outcomes cannot be inferred from antibiotic dose alone when background metal levels vary, underscoring the need to explicitly incorporate metal gradients in mixture risk assessment. • Mn background reorganizes tetracycline interactions: mitigation→sensitization. • Bootstrap breakpoints (B = 2000, seed = 9811) support a Mn transition band. • ΔBliss landscapes map regime-dependent patterns across a 5 × 5 dose surface. • PCA validates multivariate structure; ZIP (δZIP) is a robustness check in SI. • A regime-based view links metal background to mixture-risk interpretation.
Tu et al. (Wed,) studied this question.