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Related Experiment Video

Updated: Mar 24, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

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An autonomous system for multi-objective continuous evolution at scale.

Ryan M Boileau, Stefan M Golas, Qianni Ma

    Biorxiv : the Preprint Server for Biology
    |March 23, 2026
    PubMed
    Summary
    This summary is machine-generated.

    TurboPRANCE is a robotic platform enabling multivariate selection for directed evolution, overcoming previous scalability limitations. This system generates high-resolution evolutionary data for mapping complex fitness landscapes.

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    Last Updated: Mar 24, 2026

    Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
    11:53

    Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

    Published on: December 9, 2012

    13.6K

    Area of Science:

    • Evolutionary biology
    • Synthetic biology
    • Biotechnology

    Background:

    • Natural evolution is high-dimensional, with organisms adapting to multiple pressures simultaneously.
    • Directed evolution methods often simplify this landscape to a single selection axis, limiting insights and potential engineering.
    • Phage-assisted continuous evolution (PACE) offers multivariate selection but faces scalability challenges due to individual culture requirements.

    Purpose of the Study:

    • To develop a scalable platform for multivariate directed evolution.
    • To enable high-throughput evolutionary tracking and data generation for complex fitness landscapes.
    • To overcome the limitations of previous PACE implementations regarding automation and parallelization.

    Main Methods:

    • Introduction of TurboPRANCE, an open-source robotic platform integrating independently controlled turbidostats with parallel PACE lagoons.
    • Implementation of closed-loop control, automated media formulation, programmable dosing, and adaptive scheduling for sustained, asynchronous operation.
    • Integration of Nanopore long-read sequencing with DeepVariant for population-level variant tracking and high-resolution evolutionary trajectory analysis.

    Main Results:

    • TurboPRANCE enables multiplexed selection across diverse regimes with combinatorial pressures and unbounded experimental designs.
    • The system maintains cultures at consistent, infectable densities despite unpredictable workflow demands.
    • High-resolution, time-resolved evolutionary trajectories and large parallel datasets are generated, suitable for training machine learning models.

    Conclusions:

    • TurboPRANCE significantly advances the scalability and throughput of multivariate directed evolution.
    • The platform facilitates the mapping and engineering of complex fitness landscapes at an unprecedented scale.
    • This work provides a powerful tool for fundamental evolutionary studies and applied biotechnology.