Scholarlink

<p><i>Trichanthera gigantea</i> 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 <i>T. gigantea</i> 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&#xa0;mg&#xa0;g⁻<sup>1</sup>), while the modified method was most effective for roots (83.92&#xa0;mg&#xa0;g⁻<sup>1</sup>) and stems (65.58&#xa0;mg&#xa0;g⁻<sup>1</sup>) 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 <i>T. gigantea</i>. As leaves represent the primary organ for feed applications, optimization focused on TCA/acetone-extracted leaf tissue. Short-duration sonication (10–20&#xa0;min) significantly enhanced protein recovery, whereas prolonged sonication (≥ 30&#xa0;min) reduced yields across all organs, consistent with protein degradation. The highest total protein yield was obtained after 10&#xa0;min of sonication, reaching 77.14&#xa0;mg/g of protein extracted from 1&#xa0;g of leaf tissue. Using the optimized workflow, the first LC–MS/MS-based proteomics study of <i>T. gigantea</i> 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 <i>T. gigantea</i>.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月16日

查看全文
  • Che Nur Mazadillina Che Zahari,
  • Nik Mohd Afizan Nik Abd Rahman,
  • Putera Quszay Mohamad Yusman,
  • Nur Awadah Zaladi,
  • Norsharina Md Saad,
  • Siti Rokhiyah Ahmad Usuldin,
  • Noorjahan Banu Mohammed Alitheen,
  • Nadiya Akmal Baharum,
  • Mohd Azuraidi Osman,
  • Adam Thean Chor Leow

摘要

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.