Optimization of protein extraction and functional proteome profiling of Trichanthera gigantea reveals metabolic adaptations for tropical resilience

Abstract Trichanthera gigantea is a high-protein content tropical shrub with strong potential as a local source of livestock feed. However, the absence of proteomic information limits assessment of its protein stability and functional reliability. Robust proteome profiling of woody, metabolite-rich species requires optimized protein extraction strategies. Here, the study presents the first comparative evaluation of protein extraction workflows across T. gigantea organs (leaf, stem, and root) to establish a proteomics-compatible pipeline. Protein recovery using TCA/acetone, phenol-based, and a modified extraction method was quantitatively compared and further optimized by sonication. TCA/acetone extraction produced the highest protein yield in leaves (67.38 mg g⁻ 1 ), while the modified method was most effective for roots (83.92 mg g⁻ 1 ) and stems (65.58 mg g⁻ 1 ) after normalization to tissue input. Despite its widespread use in plant proteomics, the phenol method yielded comparatively low total protein per gram of tissue in T. gigantea . As leaves represent the primary organ for feed applications, optimization focused on TCA/acetone-extracted leaf tissue. Short-duration sonication (10–20 min) significantly enhanced protein recovery, whereas prolonged sonication (≥ 30 min) reduced yields across all organs, consistent with protein degradation. The highest total protein yield was obtained after 10 min of sonication, reaching 77.14 mg/g of protein extracted from 1 g of leaf tissue. Using the optimized workflow, the first LC–MS/MS-based proteomics study of T. gigantea was performed, identifying 134 proteins predominantly associated with photosynthesis, redox homeostasis, and amino acid metabolism from its leaf tissue. These proteomic signatures reveal key metabolic nodes that may be targeted to enhance stress tolerance and protein productivity, establishing a foundational resource for future functional and applied proteomics in T. gigantea .