Multimodal cellular context enables molecular phenotyping from single-molecule trajectories

MIST, using multimodal context in live Escherichia coli, more than doubled protein-specific information versus trajectory features alone, enabling phenotype mapping from single-molecule trajectories.

• Why it matters: Motion from single-molecule tracking rarely reveals the biological process without accounting for the cellular environment, limiting molecular phenotyping from trajectories alone.
• What they did: The framework integrates trajectory dynamics, emitter properties, and cellular context into a shared phenotype space, benchmarked on a reference panel of nine proteins in live Escherichia coli.
• The result: MIST enabled de novo identification of shared transcription–translation phenotype at the nucleoid periphery and detected effects of previously uncharacterized MukB ATPase mutations in a fixed reference space without retraining.

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