{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T04:55:08Z","timestamp":1793249708076,"version":"4.5.0"},"reference-count":64,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T00:00:00Z","timestamp":1784764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31900251"],"award-info":[{"award-number":["31900251"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"award":["31900251"],"award-info":[{"award-number":["31900251"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Fundamental Research Program of Shanxi Province","award":["202403021211031"],"award-info":[{"award-number":["202403021211031"]}]},{"name":"Fundamental Research Program of Shanxi Province","award":["202203021212402"],"award-info":[{"award-number":["202203021212402"]}]},{"name":"Shanxi Normal University Graduate Curriculum Ideological and Political Education Demonstration Project","award":["2024 YJSKCSZSFK-01"],"award-info":[{"award-number":["2024 YJSKCSZSFK-01"]}]},{"award":["2024 YJSKCSZSFK-01"],"award-info":[{"award-number":["2024 YJSKCSZSFK-01"]}],"id":[{"id":"https:\/\/ror.org\/03zd3ta61","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Metabolites"],"abstract":"<jats:p>Background: Plant synthetic biology reprograms metabolic networks for the sustainable production of high-value compounds. Recent computational advances incorporate machine learning to accelerate the design-build-test-learn (DBTL) cycle, enabling more predictable and scalable engineering in photoautotrophic chassis. However, the translation of AI-generated designs into stable plant phenotypes remains constrained by incomplete plant-specific training datasets, tissue heterogeneity, and limited in vivo validation. Scope: This review examines the convergence of machine learning methods with plant metabolic engineering across four spatial engineering levels: subcellular compartmentalization, cell\/tissue\/organ-specific control, developmental or inducible regulation, and genome-level organization. Spatial omics is considered a cross-cutting validation layer, and the evidence supporting each technology is classified as plant-demonstrated, non-plant proof-of-concept, or prospective. Conclusions: Integrating predictive machine learning with spatial engineering offers promising strategies to design complex biosynthetic pathways. Hybrid approaches, combining constraint-based metabolic models with generative algorithms, reduce trial-and-error in crop engineering. Future plant synthetic biology is likely to rely increasingly on automated and data-rich workflows to support more predictable plant bioproduction.<\/jats:p>","DOI":"10.3390\/metabo16080519","type":"journal-article","created":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T17:13:17Z","timestamp":1784826797000},"page":"519","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["AI-Assisted Spatial Metabolic Engineering in Plants: Integrating Flux Design, Spatial Omics, and Synthetic Biology"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2161-0089","authenticated-orcid":false,"given":"Huize","family":"Chen","sequence":"first","affiliation":[{"name":"Shanxi Key Laboratory of Plant Macromolecules Stress Response, Taiyuan 030000, China"},{"name":"School of Life Sciences, Shanxi Normal University, Taiyuan 030000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jia","family":"Yang","sequence":"additional","affiliation":[{"name":"Shanxi Key Laboratory of Plant Macromolecules Stress Response, Taiyuan 030000, China"},{"name":"School of Life Sciences, Shanxi Normal University, Taiyuan 030000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meiting","family":"Du","sequence":"additional","affiliation":[{"name":"Shanxi Key Laboratory of Plant Macromolecules Stress Response, Taiyuan 030000, China"},{"name":"School of Life Sciences, Shanxi Normal University, Taiyuan 030000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Wagh, S.G., Patil, A.M., Patil, G.B., Bhor, S.A., Pawar, K.R., and Shinde, H. 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