Software supporting "Mapping the complete biochemical landscape of carbonic anhydrase with machine-learning guided cell-free systems"

Open MIND · 2026-05-19

Impact of Process Interruptions in the Production of Lysates for Cell‐Free Expression Systems

Biotechnology and Bioengineering · 2026-04-05

Cell-free gene expression systems offer cell-like functionalities outside the confines of the cell, garnering increasing interest for applications from biomanufacturing to sensing. As applications expand, the need to implement economically scaled processes to produce cellular lysates grows. The protocols to produce these cellular lysates are complex, and the impact of altering many of the process variables remains understudied. Here, we set out to evaluate the effect of extended incubations at several points in the extract preparation process with the goal of identifying breakpoints that would enable flexibility in process implementation. As a model, we prepared lysates from 50 L cultures instead of typical 1 L volumes. We produced 72 lysates, 36 that were incubated overnight before and after culture centrifugation, and 36 that were incubated with and without a run-off reaction, each across different temperatures. We found that incubations before and after culture centrifugation substantially increased variability between culture replicates but did not reduce cell-free protein synthesis activity, contrary to conventional wisdom that materials should be kept cold as much as possible throughout the process. We also observed that omitting the run-off reaction reduced yields but resulted in lysates that were robust to incubation up to room temperature overnight. When a run-off reaction was included, activity dropped both as a function of duration and temperature, and the overall variability increased. Our work offers potential options for flexibility in implementing lysate production processes and motivates further investigation into how key processing steps relate to cell-free expression activity.

Software supporting "Mapping the complete biochemical landscape of carbonic anhydrase with machine-learning guided cell-free systems"

Zenodo (CERN European Organization for Nuclear Research) · 2026-03-06

Active learning-guided optimization of cell-free biosensors for lead testing in drinking water

bioRxiv (Cold Spring Harbor Laboratory) · 2025-08-20 · 1 citations

Point-of-use diagnostics based on allosteric transcription factors (aTFs) are promising tools for environmental monitoring and human health. However, biosensors relying on natural aTFs rarely exhibit the sensitivity and selectivity needed for real-world applications, and traditional directed evolution struggles to optimize multiple biosensor properties at once. To overcome these challenges, we develop a multi-objective, machine learning (ML)-guided cell-free gene expression workflow for engineering aTF-based biosensors. Our approach rapidly generates high-quality sequence-to-function data, which we transform into an augmented paired dataset to train an ML model using directional labels that capture how aTF mutations alter performance. We apply our workflow to engineer the aTF PbrR as a point-of-use diagnostic for lead contamination in water. We tune the sensitivity of PbrR to sense at the U.S. Environmental Protection Agency (EPA) action level for lead and modify the selectivity away from zinc, a common metal found in water supplies. Finally, we show that the engineered PbrR functions in freeze-dried cell-free reactions, enabling a diagnostic capable of detecting lead in drinking water down to ~5.7 ppb. Our ML-driven, multi-objective framework-powered by directional tokens-can generalize to other biosensors and proteins, accelerating the development of synthetic biology tools for biotechnology applications.

Semiautomated Production of Cell-Free Biosensors

ACS Synthetic Biology · 2025-03-12 · 10 citations

diagnostic technologies for the detection of chemical compounds, such as toxins and human health biomarkers. They have several advantages over conventional laboratory-based diagnostic approaches, including the ability to be assembled, freeze-dried, distributed, and then used at the point of need. This makes them an attractive platform for cheap and rapid chemical detection across the globe. Though promising, a major challenge is scaling up biosensor manufacturing to meet the needs of their multiple uses. Currently, cell-free biosensor assembly during lab-scale development is mostly performed manually by the operator, leading to quality control and performance variability issues. Here we explore the use of liquid-handling robotics to manufacture cell-free biosensor reactions. We compare both manual and semiautomated reaction assembly approaches using the Opentrons OT-2 liquid handling platform on two different cell-free gene expression assay systems that constitutively produce colorimetric (LacZ) or fluorescent (GFP) signals. We test the designed protocol by constructing an entire 384-well plate of fluoride-sensing cell-free biosensors and demonstrate that they perform close to expected detection outcomes.

A synthetic cell-free pathway for biocatalytic upgrading of formate from electrochemically reduced CO2

Nature Chemical Engineering · 2025-12-22 · 2 citations

Active learning-guided optimization of cell-free biosensors for lead testing in drinking water

Nature Communications · 2025-12-20 · 5 citations

Point-of-use diagnostics based on allosteric transcription factors (aTFs) are promising tools for environmental monitoring and human health. However, biosensors relying on natural aTFs rarely exhibit the sensitivity and selectivity needed for real-world applications, and traditional directed evolution struggles to optimize multiple biosensor properties at once. To overcome these challenges, we develop a multi-objective, machine learning (ML)-guided cell-free gene expression workflow for engineering aTF-based biosensors. Our approach rapidly generates high-quality sequence-to-function data, which we transform into an augmented paired dataset to train an ML model using directional labels that capture how aTF mutations alter performance. We apply our workflow to engineer the aTF PbrR as a point-of-use diagnostic for lead contamination in water. We tune the sensitivity of PbrR to sense at the U.S. Environmental Protection Agency (EPA) action level for lead and modify the selectivity away from zinc, a common metal found in water supplies. Finally, we show that the engineered PbrR functions in freeze-dried cell-free reactions, enabling a diagnostic capable of detecting lead in drinking water down to ~5.7 ppb. Our ML-driven, multi-objective framework powered by directional tokens can generalize to other biosensors and proteins, accelerating the development of synthetic biology tools for biotechnology applications.

A Scalable Cell-Free Manufacturing Platform for Two-Step Bioproduction of Immunogenic Conjugate Vaccines

ACS Synthetic Biology · 2025-11-19

serotype 4 capsular polysaccharide, confirming the immunogenicity of the conjugate. We anticipate that this cell-free platform will advance efforts in decentralized manufacturing and rapid response to bacterial disease threats.

Cell-Free Expression of Soluble Leafhopper Proteins from Brochosomes

ACS Synthetic Biology · 2025-03-07 · 1 citations

Brochosomes are proteinaceous nanostructures produced by leafhopper insects with superhydrophobic and antireflective properties. Unfortunately, the production and study of brochosome-based materials has been limited by poor understanding of their major constituent subunit proteins, known as brochosomins, as well as their sensitivity to redox conditions due to essential disulfide bonds. Here, we used cell-free gene expression (CFE) to achieve recombinant production and analysis of brochosomin proteins. Through the optimization of redox environment, reaction temperature, and disulfide bond isomerase concentration, we achieved soluble brochosomin yields of up to 341 ± 30 μg/mL. Analysis using dynamic light scattering and transmission electron microscopy revealed distinct aggregation patterns among cell-free mixtures with different expressed brochosomins. We anticipate that the CFE methods developed here will accelerate the ability to change the geometries and properties of natural and modified brochosomes, as well as facilitate the expression and structural analysis of other poorly understood protein complexes.