Microalgal biochemical composition dynamics and gene expression in response to bacterial quorum sensing signals

Abstract

Microalgae are promising resources for biofuels and bioproducts due to their ability to accumulate high-value metabolites such as lipids and polysaccharides. To enhance the production of these target bioproducts, an emerging strategy is to harness bacterial quorum sensing signals (QSSs) as cross-kingdom cues to steer algal metabolism, rather than relying solely on stress regimes or genetic modification, which can slow growth or cause regulatory limitations. N-acyl homoserine lactones (AHLs), particularly those present in activated sludge, are natural signaling molecules that may reprogram microalgal metabolism. However, the transcriptomic effects and species-specific responses to these signals remain poorly understood. In this study, three model microalgal strains—Chlamydomonas reinhardtii, Chlorella vulgaris, and Scenedesmus quadricauda— were exposed to pure N-hexanoyl-L-homoserine lactone (C6-HSL) and activated sludge-derived AHLs (AS-AHLs) to evaluate their potential for metabolic steering. Transcriptomic and phenotypic analyses revealed species-specific metabolic responses to AHLs. Fatty acid synthesis genes were upregulated mainly in Chlorella and Scenedesmus, supporting increased lipid accumulation, while Chlamydomonas redirected part of carbon flux toward polysaccharide biosynthesis. Lipid content increased by up to 26%, and polysaccharides by 45% in Chlamydomonas. Scenedesmus showed the highest lipid accumulation increase, reaching 33%. Meanwhile, C6-HSL treatment led to significant changes in gene expression, particularly suppression of TCA cycle and DNA replication genes in Chlamydomonas and Chlorella, consistent with a shift toward energy conservation. In contrast, Scenedesmus showed minimal transcriptional changes, suggesting greater metabolic stability. Additionally, AHLs promoted microalgal aggregation, potentially aiding biomass harvesting. These findings highlight potentials of leveraging microbial signals to manipulate algal metabolic outputs.