CRISPR-driven texture engineering: Redefining functional foods for precision nutrition and human health
Food texture is increasingly recognized as a determinant of nutritional safety, metabolic regulation, and overall health. However, conventional approaches to texture modification rely primarily on hydrocolloids, mechanical processing, or extrusion, which provide limited control over the molecular structures that govern swallowing behavior, digestibility, satiety, and nutrient release. Recent advances in CRISPR genome editing provide an opportunity to redesign texture at its biochemical foundation, enabling precise modification of starch architecture, gluten networks, and plant cell-wall components. This review synthesizes current evidence on CRISPR-enabled texture engineering and examines its relevance for vulnerable populations and chronic disease management. Gene edits that adjust amylose–amylopectin ratios or gluten epitope profiles influence glycemic responses, allergenicity, and dough quality. Modifications to cell-wall remodeling enzymes reshape firmness, hydration, and breakdown behavior in fruits and vegetables. These molecular interventions create new pathways for designing safer foods for dysphagia, tailored textures for clinical nutrition, and structured matrices that support glycemic control, satiety, or gut health. Beyond clinical contexts, CRISPR-guided texture design holds promise for sustainability, performance nutrition, and AI-driven precision diet formulation. These developments position texture as a programmable variable in next-generation functional foods. • CRISPR enables genetic control of texture-relevant starch, protein, and cell-wall structures. • Molecular texture design improves safety and nutrient delivery in dysphagia and clinical diets. • Gene-edited starch architectures support glycemic control and metabolic health strategies. • Reduced-epitope gluten edits lower immunoreactivity while preserving dough functionality. • Texture engineering aligns with sustainability, performance nutrition, and AI-guided diet design.
Authors
- Jacob Tizhe Liberty (ORCID: https://orcid.org/0000-0001-7218-2921)
- Fatemah B. Alsalman (ORCID: https://orcid.org/0000-0001-6555-8468)
- Haijiao Lin
- Xin Zhao
Institutions
- Espace pour la vie (CA)
- Kuwait Institute for Scientific Research (KW)
- McGill University (CA)
Publication Details
- Journal
- Journal of Functional Foods
- Published
- 2026-03-12
- DOI
- https://doi.org/10.1016/j.jff.2026.107248
- Primary Topic
- Food composition and properties
- Type
- article
- Field-Weighted Citation Impact
- 0.00