Search NASA⌕ Search
Home/Archive/DOE OSTI

DOE OSTI · 3021406

Automated Strain Construction for Biosynthetic Pathway Screening in Yeast

Astolfi, Maria C. T. [University of California, Berkeley, CA (United States); Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]·Yoder, Sam D. [Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]·Delfa-Lalaguna, Marina [Joint BioEnergy Institute; Faculty of Chemical Sciences; Complutense University of Madrid]·Winegar, Peter H. [Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); University of California, Berkeley, CA (United States)] (ORCID:0000000309844990)·Holm, Sara K. F. [Technical University of Denmark, Lyngby (Denmark); Joint BioEnergy Institute (JBEI), Emeryville, CA (United States)]·Lei, Mengziang [Joint BioEnergy Institute (JBEI), Emeryville, CA (United States)]·Zhao, Xixi [Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); University of California, Berkeley, CA (United States)]·Tan, Stephen E. [Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]·Louie, Randy [Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]·Hillson, Nathan J. [Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:0000000291693978)·Hudson, Graham A. [Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); University of California, Berkeley, CA (United States)] (ORCID:0000000237154279)·Keasling, Jay D. [University of California, Berkeley, CA (United States); Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Technical University of Denmark, Lyngby (Denmark)] (ORCID:0000000341706088)
View original source ↗Read source document ↗Export metadata ↓

Abstract

Automation accelerates the Design-Build-Test-Learn (DBTL) cycle for synthetic biology; however, most strain construction pipelines lack robotic integration. Here, in this study, we present the workflow design and source code for a modular, integrated protocol that automates the Build step in Saccharomyces cerevisiae. We programmed the Hamilton Microlab VANTAGE to integrate off-deck hardware via its central robotic arm, enabling automated steps that increased throughput to 2,000 transformations per week. We developed a user interface with the Hamilton VENUS software to support on-demand parameter customization. As a proof of concept, we screened a gene library in an engineered yeast strain producing verazine, a key intermediate in the biosynthesis of steroidal alkaloids. Our pipeline rapidly identified pathway bottlenecks and genes that enhanced verazine production by 2.0- to 5-fold. This technical note provides resources for synthetic biologists designing yeast workflows for biofoundries to screen libraries for pathway discovery/optimization, combinatorial biosynthesis, and protein engineering.

Explore related subjects

automationhigh-throughput screenmetabolic engineeringmicrobial biosynthesisrobotics integrationstrain engineering

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Astolfi, Maria C. T. [University of California, Berkeley, CA (United States); Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Yoder, Sam D. [Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Delfa-Lalaguna, Marina [Joint BioEnergy Institute; Faculty of Chemical Sciences; Complutense University of Madrid], Winegar, Peter H. [Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); University of California, Berkeley, CA (United States)] (ORCID:0000000309844990), Holm, Sara K. F. [Technical University of Denmark, Lyngby (Denmark); Joint BioEnergy Institute (JBEI), Emeryville, CA (United States)], Lei, Mengziang [Joint BioEnergy Institute (JBEI), Emeryville, CA (United States)], Zhao, Xixi [Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); University of California, Berkeley, CA (United States)], Tan, Stephen E. [Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Louie, Randy [Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Hillson, Nathan J. [Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:0000000291693978), Hudson, Graham A. [Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); University of California, Berkeley, CA (United States)] (ORCID:0000000237154279), Keasling, Jay D. [University of California, Berkeley, CA (United States); Joint BioEnergy Institute (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Technical University of Denmark, Lyngby (Denmark)] (ORCID:0000000341706088). 2025-10-08. Automated Strain Construction for Biosynthetic Pathway Screening in Yeast. https://doi.org/10.1021/acssynbio.5c00554

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

DOE OSTI2026

A Smart Vision-Aided RICH (Robotic Interface Control and Handling) System for VULCAN

High-flux neutron beams and high-efficiency detectors enable rapid neutron diffraction measurements at the Engineering Materials Diffractometer (VULCAN) at the Spallation Neutron Source (SNS), Oak Ridge National Laboratory (ORNL). To optimize beam time utilization, efficient sample exchange, alignment, and automated measurements are essential. Recent advances in artificial intelligence (AI) have expanded the capabilities of robotic systems. Here, we report the development of a Robotic Interactive Control and Handling (RICH) system for sample handling at VULCAN, designed to support high-throughput experiments and reduce overhead time. The RICH system employs a six-axis desktop robot integrated with AI-based computer vision models capable of recognizing and localizing samples in real time from instrument and depth-resolving cameras. Vision algorithms combine these detections to align samples with designated measurement positions or place them within complex sample environments such as furnaces. This integration of machine learning-assisted vision with robotic handling demonstrates the feasibility of autonomous sample detection and preparation, offering a pathway toward fully unmanned neutron scattering experiments.

automation↗
DOE OSTI2025

Pyomo: Accidentally outrunning the bear

Pyomo is an open-source optimization modeling software that has undergone significant evolution since its inception in 2008. Pyomo has evolved to enhance flexibility, solver integration, and community engagement. Modern collaborative tools for open-source software have facilitated the development of new Pyomo functionality and improved our development process through automated testing and performance-tracking pipelines. However, Pyomo faces challenges typical of research software, including resource limitations and knowledge retention. The Pyomo team’s commitment to better development practices and community engagement reflects a proactive approach to these issues. We describe Pyomo’s development journey, highlighting both successes and failures, in the hopes that other open-source research software packages may benefit from our experiences.

automation↗
DOE OSTI2024

Autonomous Energy Systems: Building Reliable, Resilient, and Secure Electrified Communities

Technological changes across energy systems are forcing utilities and operators to reconsider their methods for managing power delivery, but few operators have adopted advanced controls and operational software. Their challenge is that every system has peculiar requirements, and the available solutions are relatively new, untested, and difficult to integrate into an operational environment. Through extensive collaboration with utilities and cooperatives, the National Renewable Energy Laboratory has realized the need for autonomous and optimized management of energy resources, leading to the development of Autonomous Energy Systems, a packaged set of controls that is ready to be integrated into existing control rooms.

automation↗