Assessing combinatorial diversity of aureochrome bZIPs through genome-wide screening
Aureochromes are unique blue light-responsive LOV (Light Oxygen Voltage) photoreceptors cum basic leucine zipper (bZIP) transcription factors (TFs), present exclusively in photosynthetic marine stramenopiles. Considering the availability of the complete genome sequence, this study focuses particularly on aureochromes from Ectocaupus siliculosus. Aureochromes mediate light-regulated developmental responses in this brown photosynthetic algae. Both the LOV sensor and the bZIP effector shows sequence-structure conservation. The LOV+bZIP modules of aureochrome homologs/ paralogs are not only structurally similar but also show an identical oligomeric state -- preferably dimeric. Aureochromes execute diverse cellular responses in different photosynthetic stramenopiles-- though their activities can vary even within a given algal species. Besides a heterogeneous linker connecting the sensor-effector and a flexible N-terminal region, the sequence composition of both the domains is vital. Therefore, it is important to understand whether aureochromes select dimerization partners from the same family or interact with other bZIPs as well. To regulate multifarious bio-logical activities, it is possible that aureochromes activate the global TF interaction network. Following homo/heterodimer modeling, we address the compatibility of dimerization partners by screening through heptad repeats. We evaluate the dimer interface area in terms of gain in solvation energy as well as the number of hydrogen bonds/salt bridge interactions. We further explore the relative stability of these structures from a graph-theoretic perspective through well-studied measures such as the energy of the graph and average participation coefficient. Furthermore, we also conduct an information-theoretic analysis using network information centrality and Kullback-Leibler divergence. We find that all our investigations into the relative stability of these dimers using diverse methods from bioinformatics, network science, and, information theory are in harmonious agreement. Our approach and findings should facilitate the design of experiments.