Using a Novel Multiplexed Algal Cytological Imaging (MACI) Assay and Machine Learning as a Way to Characterize...

Area of Science:

• Environmental toxicology
• Cellular imaging
• Phycology

Background:

• High-throughput phenotypic profiling characterizes single-cell morphological data for predicting chemical targets and mechanisms of action (MoAs).
• This approach is underutilized in environmental toxicology due to limited studies in relevant species.

Purpose of the Study:

• To develop and validate a multiplexed algal cytological imaging (MACI) assay for environmental toxicology.
• To characterize cellular impacts and determine MoAs of environmental chemicals in algae.

Main Methods:

• Developed a MACI assay using the unicellular microalgae *Raphidocelis subcapitata*.
• Exposed *R. subcapitata* to herbicides and antibiotics with known MoAs.
• Quantified subtle changes in subcellular component morphology, including area, shape, quantity, fluorescence, and granularity.

Main Results:

• The MACI assay successfully characterized phenotypic responses to various chemicals.
• Detected subtle morphological alterations in subcellular components.
• Demonstrated the assay's ability to differentiate responses based on chemical MoAs.

Conclusions:

• MACI provides a rapid and effective framework for analyzing phenotypic responses to environmental chemicals.
• The assay can be used to determine MoAs and identify cellular targets in plant-type organisms.
• MACI advances the application of high-throughput phenotypic profiling in environmental toxicology.