Transcriptome and Redox Proteome Reveal Temporal Scales of Carbon Metabolism Regulation in Model Cyanobacteria Under Light Disturbance
Connah G. M. Johnson, Zachary Johnson, Liam S. Mackey, Xiaolu Li, Natalie C. Sadler, Tong Zhang, Wei-Jun Qian, Pavlo Bohutskyi, Song Feng, Margaret S. Cheung

TL;DR
This study introduces a systems approach combining energy-landscape concepts and machine learning to analyze redox and conformational dynamics in cyanobacteria's response to light disturbance, revealing rapid redox changes in key regulatory proteins.
Contribution
It presents a novel, interpretable modeling workflow that integrates redox proteome analysis with gene expression data to uncover regulatory mechanisms under environmental stress.
Findings
Redox shifts in regulatory proteins occur rapidly under light disturbance.
Minimal changes in protein abundance suggest redox modifications drive regulation.
Redox dynamics link electron transport with circadian rhythms.
Abstract
We develop a systems approach based on an energy-landscape concept to differentiate interactions involving redox activities and conformational changes of proteins and nucleic acids interactions in multi-layered protein-DNA regulatory networks under light disturbance. Our approach is a data-driven modeling workflow using a physics-informed machine learning algorithm to train a non-linear mathematical model for interpreting gene expression dynamics and to lead discovery for protein regulators using redox proteome analysis. We distinguish light-responsive elements within central carbon metabolism pathways from independent variables like circadian time using the publicly available transcriptome datasets of Synechococcus elongatus over diel cycles responding to light perturbations. Our approach provides interpretable de novo models for elucidating events of reactions in complex regulatory…
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Taxonomy
TopicsPhotosynthetic Processes and Mechanisms · Algal biology and biofuel production · Metabolomics and Mass Spectrometry Studies
