Pipette, mix, repeat: A reduced-order fluid model and protocol survey to evaluate 96-well mixing protocols

Area of Science:

• Fluid dynamics
• Biotechnology
• Biochemistry

Background:

• Pipetting up and down is a fundamental mixing technique in 96-well plates for biological and bioengineering applications.
• Current mixing protocols lack quantitative justification, relying on rules of thumb like 'three mixing cycles' or arbitrary stroke counts (2-20).
• Limited fluid-mechanical guidance exists for optimizing pipetting strategies to ensure adequate mixing.

Purpose of the Study:

• To develop and validate a reduced-order model for quantifying mixing efficiency in 96-well plates based on pipetting parameters.
• To investigate the impact of pipette jet characteristics (strength, footprint, angle, placement) on mixing.
• To compare model predictions with existing pipetting practices and provide guidance for protocol optimization.

Main Methods:

• Developed a reduced-order compartment model simulating advection-diffusion in a 96-well plate.
• Represented pipetting as a localized exchange enhancement parameterized by jet strength, footprint size, angle, and tip placement.
• Quantified mixing by measuring the decay of normalized concentration variance after simulated aspirate-dispense cycles.
• Conducted a survey of existing pipetting protocols from research forums, commercial assays, and publications.

Main Results:

• The model qualitatively reproduced mixing hierarchies seen in high-fidelity simulations.
• Higher jet strength and larger jet footprint significantly accelerated homogenization.
• Gentle, small-footprint jets frequently required more than three cycles for near-uniform mixing.
• Pipette angle and tip position had minor effects compared to jet strength and footprint size.
• Survey revealed a wide variation in recommended strokes (2-20) with no consensus.

Conclusions:

• Three mixing cycles are often insufficient for effective homogenization in 96-well plates.
• The developed model offers a fast, interpretable tool for rationalizing and redesigning pipette-mixing protocols.
• Optimizing pipetting parameters like jet strength and footprint size is crucial for efficient mixing in high-throughput experiments.