Shahid Mukhtar Lab is broadly interested in interdisciplinary research projects at the interface of plant network biology, bioinformatics, computational modelling and dynamical interactions between plant hosts and their microbiomes. The long-term goal of the Shahid Mukhtar Lab is to understand how macromolecular networks control biological processes and how environmental perturbations in such networks can explain diverse phenotypes. The current projects under investigation include:
Dynamics of Transcriptional Regulatory Networks in Plant Defense
In any eukaryotic cell, thousands of genes and their products orchestrate their transcriptional activities to create cellular functions, phenotypic plasticity and organismal fecundity. Functional modules embedded within protein–DNA interactions networks execute diverse cellular functions. The dichotomous (deterministic or stochastic) nature of network modules is beneficial to cells or organisms for adaptation to physiological perturbations, environmental cues, or pathological signals. As with any host–pathogen conflict, plants and their pathogens are in an evolutionary “arms race,” in which the host mounts defenses, the pathogen develops new strategies to thwart the defensive mechanisms, which in turn forces the host to adapt. Currently, Shahid Mukhtar Lab is developing a platform by integrating existing and novel computational tools and algorithms that can be exploited to predict, model and determine the dynamics of plant immune regulatory networks.
Microbial Community Transcriptional Networks
Plants are hosts to diverse microbial communities that have been shown to contribute to a variety of plant processes such as growth and disease resistance. Plant microbiomes may colonize external and internal tissues in both above and below ground environments. While the relationships between roots and soil microbiota have been extensively studied, little is known about the composition and function of the phyllosphere, or leaf, microbiome. The phyllosphere microbiome is much more dynamic than the soil microbiome due to its exposure to rapidly changing environmental factors such as wind, temperature, and moisture. Microbiome composition may additionally be affected by the plant genotype and age. However, these factors may be utilized to explore how plant-derived compounds such as hormones affect microbial diversity and how the plants may recruit certain species of microbes under different conditions. Shahid Mukhtar Lab is conducting a broad scale study of the leaf microbiome in model species.
Predictive Modeling to Identify Key Functionalities in Host-Pathogen Interactions
Network analysis has been a recent focus in biological sciences due to its ability to synthesize global visualizations of cellular processes and predict functions based on inferences from network properties. In the context of the network visualization, a protein is represented by a node and the interactions between proteins are described by lines, or edges, connecting the nodes. A grouping of highly connected nodes is referred to as a hub and generally indicates that the nodes within a hub are involved in a similar functional process. Proteins with a high degree are typically evolutionarily conserved, essential components of overall cellular function. Malfunctions in these proteins result in disease phenotypes and may be targets for pathogen virulence. Two additional widely used measures of centrality are betweenness centrality and eigenvector centrality. Currently, Shahid Mukhtar Lab is performing network analyses on the currently available interactome data in Arabidopsis and aim to predict key functionalities.