Multi-omic and phenotypic analysis of growth and resilience of open raceway pond production of Monoraphidium minutum 26B-AM

Green microalgae, such as Monoraphidium minutum 26B-AM, have garnered significant commercial interest due to high biomass production and lipid yield, providing promising candidates for various bioprocessing applications. However, the economic viability of large-scale algal cultivation in open raceway ponds is challenged by biocontamination and environmental stressors, necessitating deeper understanding of the molecular mechanisms that underpin resilience and productivity in these systems. We hypothesized that the molecular signature associated with the cellular responses of M. minutum to environmental stressors will reveal critical information for the timely prediction of resilience and productivity in algal cultures within open pond systems. To test this hypothesis, we performed a pilot study involving a multi-omic time-course approach, integrating transcriptomics, proteomics, metabolomics, and phenomics, to monitor the acclimation, growth dynamics, and pathogen responses of algal cultures in two 1000L raceway ponds, before and after the introduction of a pathogen as a stressor. We identified a number of molecular patterns that correlate with changes in the algal environment, and we can track these changes longitudinally across the ponds. Furthermore, we propose a way to focus on transition-specific molecular pathways through integrated multi-omics, showing that most patterns are unique to each studies stressor and growth transition. Ultimately, this study suggests the further use of multi-omics observations at scale, laying the groundwork for developing molecular detection techniques and predictive models that can improve the sustainability and efficiency of large-scale algae biomass production.