Slow poisoning and destruction of networks: edge proximity and its implications for biological and infrastructure networks

Diverse gut pathogens exploit the host engulfment pathway via a conserved mechanism

Macrophages clear infections by engulfing and digesting pathogens within phagolysosomes. Pathogens escape this fate by engaging in a molecular arms race; they use WxxxE motif-containing "effector" proteins to subvert the host cells they invade and seek refuge within protective vacuoles. Here, we define the host component of the molecular arms race as an evolutionarily conserved polar "hot spot" on the PH domain of ELMO1 (Engulfment and Cell Motility protein 1), which is targeted by diverse WxxxE effectors. Using homology modeling and site-directed mutagenesis, we show that a lysine triad within the "patch" directly binds all WxxxE effectors tested: SifA (Salmonella), IpgB1 and IpgB2 (Shigella), and Map (enteropathogenic Escherichia coli). Using an integrated SifA-host protein-protein interaction network, in silico network perturbation, and functional studies, we show that the major consequences of preventing SifA-ELMO1 interaction are reduced Rac1 activity and microbial invasion. That multiple effectors of diverse structure, function, and sequence bind the same hot spot on ELMO1 suggests that the WxxxE effector(s)-ELMO1 interface is a convergence point of intrusion detection and/or host vulnerability. We conclude that the interface may represent the fault line in coevolved molecular adaptations between pathogens and the host, and its disruption may serve as a therapeutic strategy.

Diverse Gut Pathogens Exploit the Host Engulfment Pathway via a Conserved Mechanism

Macrophages clear infections by engulfing and digesting pathogens within phagolysosomes. Pathogens escape this fate by engaging in a molecular arms race; they use WxxxE motif-containing effector proteins to subvert the host cells they invade and seek refuge within protective vacuoles. Here we define the host component of the molecular arms race as an evolutionarily conserved polar hotspot on the PH-domain of ELMO1 (Engulfment and Cell Motility1), which is targeted by diverse WxxxE-effectors. Using homology modeling and site-directed mutagenesis, we show that a lysine triad within the patch directly binds all WxxxE-effectors tested: SifA (Salmonella), IpgB1 and IpgB2 (Shigella), and Map (enteropathogenic E. coli). Using an integrated SifA-host protein-protein interaction (PPI) network, in-silico network perturbation, and functional studies we show that the major consequences of preventing SifA-ELMO1 interaction are reduced Rac1 activity and microbial invasion. That multiple effectors of diverse structure, function, and sequence bind the same hotpot on ELMO1 suggests that the WxxxE-effector(s)-ELMO1 interface is a convergence point of intrusion detection and/or host vulnerability. We conclude that the interface may represent the fault line in co-evolved molecular adaptations between pathogens and the host and its disruption may serve as a therapeutic strategy.

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.

Structural Basis of Design and Engineering for Advanced Plant Optogenetics

In optogenetics, light-sensitive proteins are specifically expressed in target cells and light is used to precisely control the activity of these proteins at high spatiotemporal resolution. Optogenetics initially used naturally occurring photoreceptors to control neural circuits, but has expanded to include carefully designed and engineered photoreceptors. Several optogenetic constructs are based on plant photoreceptors, but their application to plant systems has been limited. Here, we present perspectives on the development of plant optogenetics, considering different levels of design complexity. We discuss how general principles of light-driven signal transduction can be coupled with approaches for engineering protein folding to develop novel optogenetic tools. Finally, we explore how the use of computation, networks, circular permutation, and directed evolution could enrich optogenetics.

Role of a 19S Proteasome Subunit- PSMD10Gankyrin in Neurogenesis of Human Neural Progenitor Cells

PSMD10^Gankyrin, a proteasome assembly chaperone, is a widely known oncoprotein which aspects many hall mark properties of cancer. However, except proteasome assembly chaperon function its role in normal cell function remains unknown. To address this issue, we induced PSMD10^Gankyrin overexpression in HEK293 cells and the resultant large-scale changes in gene expression profile were analyzed. We constituted networks from microarray data of these differentially expressed genes and carried out extensive topological analyses. The overrecurring yet consistent theme that appeared throughout analysis using varied network metrics is that all genes and interactions identified as important would be involved in neurogenesis and neuronal development. Intrigued we tested the possibility that PSMD10^Gankyrin may be strongly associated with cell fate decisions that commit neural stem cells to differentiate into neurons. Overexpression of PSMD10^Gankyrin in human neural progenitor cells facilitated neuronal differentiation via β-catenin Ngn1 pathway. Here for the first time we provide preliminary and yet compelling experimental evidence for the involvement of a potential oncoprotein – PSMD10^Gankyrin, in neuronal differentiation.

Modeling Bacteria-Phage Interactions and Its Implications for Phage Therapy

Bacteriophages are more abundant than any other organism on our planet. The interaction of bacteriophages and bacteria and their coevolution is well known. In this chapter, we describe various aspects of modeling such systems and their dynamics. We explore their interaction in: (i) liquid media, which leads to well-mixed populations and (ii) solid media, where their interaction is spatially restricted. Such modeling, when used in conjunction with experiments would not only shed deep insight into the underlying dynamics but also provide useful clues toward potential therapeutic applications.

Observer-Based Discrete-Time Nonnegative Edge Synchronization of Networked Systems

This paper studies the multi-input and multi-output discrete-time nonnegative edge synchronization of networked systems based on neighbors' output information. The communication relationship among the edges of networked systems is modeled by well-known line graph. Two observer-based edge synchronization algorithms are designed, for which some necessary and sufficient synchronization conditions are derived. Moreover, some computable sufficient synchronization conditions are obtained, in which the feedback matrix and the observer matrix are computed by solving the linear programming problems. We finally design several simulation examples to demonstrate the validity of the given nonnegative edge synchronization algorithms.

Using complex networks towards information retrieval and diagnostics in multidimensional imaging

We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers.

Mapping networks of light-dark transition in LOV photoreceptors

MOTIVATION

In optogenetics, designing modules of long or short signaling state lifetime is necessary for control over precise cellular events. A critical parameter for designing artificial or synthetic photoreceptors is the signaling state lifetime of photosensor modules. Design and engineering of biologically relevant artificial photoreceptors is based on signaling mechanisms characteristic of naturally occurring photoreceptors. Therefore identifying residues important for light-dark transition is a definite first step towards rational design of synthetic photoreceptors. A thorough grasp of detailed mechanisms of photo induced signaling process would be immensely helpful in understanding the behaviour of organisms.

RESULTS

Herein, we introduce the technique of differential networks. We identify key biological interactions, using light-oxygen-voltage domains of all organisms whose dark and light state crystal structures are simultaneously available. Even though structural differences between dark and light states are subtle (other than the covalent bond formation between flavin chromophore and active site Cysteine), our results successfully capture functionally relevant residues and are in complete agreement with experimental findings from literature. Additionally, using sequence-structure alignments, we predict functional significance of interactions found to be important from network perspective yet awaiting experimental validation. Our approach would not only help in minimizing extensive photo-cycle kinetics procedure but is also helpful in providing first-hand information on the fundamentals of photo-adaptation and rational design of synthetic photoreceptors in optogenetics.

CONTACT

devrani.dbs@presiuniv.ac.in or soumen@jcbose.ac.in

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.