Stress & Systems Biology
From the molecular circuits that protect plants under abiotic stress to genome-scale metabolic modelling and CRISPR-assisted pathway engineering for crop improvement.
Stress & Systems Biology Overview
Key Concepts & Equations
Superoxide generation
\( \text{O}_2 + e^- \rightarrow \text{O}_2^{\bullet -} \xrightarrow{\text{SOD}} \text{H}_2\text{O}_2 \xrightarrow{\text{CAT}} \text{H}_2\text{O} \)
Ascorbate peroxidase (APX)
\( \text{H}_2\text{O}_2 + 2\,\text{AsA} \xrightarrow{\text{APX}} 2\,\text{H}_2\text{O} + 2\,\text{MDHA} \)
FBA steady-state constraint
\( \mathbf{S} \cdot \mathbf{v} = \mathbf{0}, \quad v_{\min} \le v_i \le v_{\max} \)
Network centrality (betweenness)
\( C_B(v) = \sum_{s \ne v \ne t} \frac{\sigma_{st}(v)}{\sigma_{st}} \)
Chapters
Chapter 19: Stress Biochemistry
ROS species and antioxidant enzymes (SOD, catalase, APX), ascorbate-glutathione cycle, osmolyte accumulation (proline, glycine betaine, trehalose), heat shock proteins, cold acclimation, and heavy metal detoxification.
Chapter 20: Metabolic Engineering
Golden Rice (beta-carotene), herbicide-resistant EPSPS, Bt toxin, enhanced oil content, metabolic flux analysis (FBA: S·v = 0), CRISPR/Cas9 pathway editing, and synthetic biology tools.
Chapter 21: Systems Plant Biology
Metabolomics (GC-MS, LC-MS, NMR), transcriptomics, proteomics, 13C-MFA, genome-scale metabolic models, multi-omics integration, network analysis (centrality, hubs), and machine learning for metabolic prediction.