Network analysis of chromophore binding site in LOV domain

Photoreceptor proteins are versatile toolbox for developing biosensors for optogenetic applications. These molecular tools get activated upon illumination of blue light, which in turn offers a non-invasive method for gaining high spatiotemporal resolution and precise control of cellular signal transduction. The Light-Oxygen-Voltage (LOV) domain family of proteins is a well-recognized system for constructing optogenetic devices. Translation of these proteins into efficient cellular sensors is possible by tuning their photochemistry lifetime. However, the bottleneck is the need for more understanding of the relationship between the protein environment and photocycle kinetics. Significantly, the effect of the local environment also modulates the electronic structure of chromophore, which perturbs the electrostatic and hydrophobic interaction within the binding site. This work highlights the critical factors hidden in the protein networks, linking with their experimental photocycle kinetics. It presents an opportunity to quantitatively examine the alternation in chromophore's equilibrium geometry and identify details which have substantial implications in designing synthetic LOV constructs with desirable photocycle efficiency.

Heterogeneity in winged helix-turn-helix and substrate DNA interactions: Insights from theory and experiments

Specific interactions between transcription factors (TFs) and substrate DNA constitute the fundamental basis of gene expression. Unlike in TFs like basic helix-loop-helix or basic leucine zippers, prediction of substrate DNA is extremely challenging for helix-turn-helix (HTH). Experimental techniques like chromatin immunoprecipitation combined with massively parallel DNA sequencing remains a viable option. We characterize the molecular basis of heterogeneity in HTH-DNA interaction using in silico tools and thence validate them experimentally. Given the profound functional diversity in HTH, we focus primarily on winged-HTH (wHTH). We consider 180 wHTH TFs, whose experimental three-dimensional structures are available in DNA bound/unbound conformations. Starting with PDB-wide scanning and curation of data, we construct a phylogenetic tree, which distributes 180 wHTH sequences under multiple sub-groups. Structure-sequence alignment followed by detailed intra/intergroup analysis, covariation studies and extensive network theory analysis help us to gain deep insight into heterogeneous wHTH-substrate DNA interactions. A central aim of this study is to find a consensus to predict the substrate DNA sequence for wHTH, amidst heterogeneity. The strength of our exhaustive theoretical investigations including molecular docking are successfully tested through experimental characterization of wHTH TF from Sulfurimonas denitrificans.

Assessing Combinatorial Diversity of Aureochrome Basic Leucine Zippers through Genome-Wide Screening

Aureochromes are unique blue light-responsive light-oxygen-voltage (LOV) 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 on aureochromes from Ectocarpus siliculosus. Aureochromes mediate light-regulated developmental responses in these brown photosynthetic algae. Both the LOV sensor and the bZIP effector show overall sequence-structure conservation. The structurally similar LOV + bZIP modules of aureochrome homologs/paralogs prefer a dimeric state. Besides a heterogeneous linker connecting the sensor-effector and a flexible N-terminal region, the sequence composition of both domains is vital. Aureochromes execute diverse cellular responses in different photosynthetic stramenopiles - though their activities can vary even within a given algal species. 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 biological 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 and 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, average participation coefficient, and betweenness centrality. Furthermore, we also conduct an information-theoretic analysis using hitherto understudied measures such as network information centrality and Kullback-Leibler divergence. We find that all our investigations into the relative stability of the dimers using diverse methods from bioinformatics, network science, and information theory are in harmonious agreement. Coupling preferences of monomers in aureochromes can be further translated to design novel optogenetic tools useful for understanding human development and disease.

Network approach to mutagenesis sheds insight on phage resistance in mycobacteria

MOTIVATION

A rigorous yet general mathematical approach to mutagenesis, especially one capable of delivering systems-level perspectives would be invaluable. Such systems-level understanding of phage resistance is also highly desirable for phage-bacteria interactions and phage therapy research. Independently, the ability to distinguish between two graphs with a set of common or identical nodes and identify the implications thereof, is important in network science.

RESULTS

Herein we propose a measure called shortest path alteration fraction (SPAF) to compare any two networks by shortest paths, using sets. When SPAF is one, it can identify node pairs connected by at least one shortest path, which are present in either network but not both. Similarly, SPAF equaling zero identifies identical shortest paths, which are simultaneously present between a node pair in both networks. We study the utility of our measure theoretically in five diverse microbial species, to capture reported effects of well-studied mutations and predict new ones. We also scrutinise the effectiveness of our procedure through theoretical and experimental tests on Mycobacterium smegmatis mc2155 and by generating a mutant of mc2155, which is resistant to mycobacteriophage D29. This mutant of mc2155, which is resistant to D29 exhibits significant phenotypic alterations. Whole-genome sequencing identifies mutations, which cannot readily explain the observed phenotypes. Exhaustive analyses of protein-protein interaction network of the mutant and wild-type, using the machinery of topological metrics and differential networks does not yield a clear picture. However, SPAF coherently identifies pairs of proteins at the end of a subset of shortest paths, from amongst hundreds of thousands of viable shortest paths in the networks. The altered functions associated with the protein pairs are strongly correlated with the observed phenotypes.

Mass Testing and Proactiveness Affect Epidemic Spreading

The detection and management of diseases become quite complicated when pathogens contain asymptomatic phenotypes amongst their ranks, as evident during the recent COVID-19 pandemic. Spreading of diseases has been studied extensively under the paradigm of susceptible-infected-recovered-deceased (SIRD) dynamics. Various game-theoretic approaches have also addressed disease spread, many of which consider S , I , R , and D as strategies rather than as states. Remarkably, most studies from the above approaches do not account for the distinction between the symptomatic or asymptomatic aspect of the disease. It is well-known that precautionary measures like washing hands, wearing masks and social distancing significantly mitigate the spread of many contagious diseases. Herein, we consider the adoption of such precautions as strategies and treat S , I , R , and D as states. We also attempt to capture the differences in epidemic spreading arising from symptomatic and asymptomatic diseases on various network topologies. Through extensive computer simulations, we examine that the cost of maintaining precautionary measures as well as the extent of mass testing in a population affects the final fraction of socially responsible individuals. We observe that the lack of mass testing could potentially lead to a pandemic in case of asymptomatic diseases. Network topology also seems to play an important role. We further observe that the final fraction of proactive individuals depends on the initial fraction of both infected as well as proactive individuals. Additionally, edge density can significantly influence the overall outcome. Our findings are in broad agreement with the lessons learnt from the ongoing COVID-19 pandemic.