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A high-throughput multiparameter screen for accelerated development and optimization of soluble genetically encoded fluorescent biosensors.

Nature communications | 2022

Genetically encoded fluorescent biosensors are powerful tools used to track chemical processes in intact biological systems. However, the development and optimization of biosensors remains a challenging and labor-intensive process, primarily due to technical limitations of methods for screening candidate biosensors. Here we describe a screening modality that combines droplet microfluidics and automated fluorescence imaging to provide an order of magnitude increase in screening throughput. Moreover, unlike current techniques that are limited to screening for a single biosensor feature at a time (e.g. brightness), our method enables evaluation of multiple features (e.g. contrast, affinity, specificity) in parallel. Because biosensor features can covary, this capability is essential for rapid optimization. We use this system to generate a high-performance biosensor for lactate that can be used to quantify intracellular lactate concentrations. This biosensor, named LiLac, constitutes a significant advance in metabolite sensing and demonstrates the power of our screening approach.

Pubmed ID: 35614105 RIS Download

Research resources used in this publication

None found

Antibodies used in this publication

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Associated grants

  • Agency: NIGMS NIH HHS, United States
    Id: R01 GM124038
  • Agency: NIGMS NIH HHS, United States
    Id: F32 GM123577
  • Agency: NEI NIH HHS, United States
    Id: P30 EY012196
  • Agency: NCI NIH HHS, United States
    Id: F31 CA254162
  • Agency: NINDS NIH HHS, United States
    Id: F32 NS116105

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