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BRIEF RESEARCH REPORT article

Front. Bioeng. Biotechnol.

Sec. Synthetic Biology

Volume 13 - 2025 | doi: 10.3389/fbioe.2025.1560200

Developing a model system to sustain ex vivo chloroplast function

Provisionally accepted
  • 1 Lawrence Livermore National Laboratory (DOE), Livermore, United States
  • 2 Georgetown College, Georgetown University, Washington, D.C., District of Columbia, United States

The final, formatted version of the article will be published soon.

    Chloroplasts are critical organelles in plants and algae responsible for accumulating biomass through photosynthetic carbon fixation and cellular maintenance through metabolism in the cell. Chloroplasts are increasingly appreciated for their role in biomanufacturing, as they can produce many useful molecules, and a deeper understanding of chloroplast regulation and function would provide more insight for the biotechnological applications of these organelles. However, traditional genetic approaches to manipulate chloroplasts are slow, and generation of transgenic organisms to study their function can take weeks to months, significantly delaying the pace of research. To develop chloroplasts themselves as a quicker and more defined platform, we isolated chloroplasts from the green algae, Chlamydomonas reinhardtii, and examined their photosynthetic function after extraction. Combined with a metabolic modeling approach using flux-balance analysis, we identified key metabolic reactions essential to chloroplast function and leveraged this information into reagents that can be used in a “chloroplast media” capable of maintaining chloroplast photosynthetic function over time ex vivo compared to buffer alone. We envision this could serve as a model platform to enable more rapid design-build-test-learn cycles to study and improve chloroplast function in combination with genetic modifications and potentially as a starting point for the bottom-up design of a synthetic organelle-containing cell.

    Keywords: chloroplast, Chlamydomonas reinhardtii, metabolic modeling, Photosynthesis, Flux balance analysis (FBA)

    Received: 14 Jan 2025; Accepted: 19 Mar 2025.

    Copyright: © 2025 Mohagheghi, Navid, Mossington, Ye, Coleman and Hoang-Phou. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Steven Hoang-Phou, Lawrence Livermore National Laboratory (DOE), Livermore, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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