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Marko Djordjevic - PhD, Associate Professor
 

Research interest

Our research is on biophysical modeling and bioinformtics. We often combine these two, which results in an approach where development of bioinformatic methods is facilitated by physical understanding of the underlying biological processes. Current research is outlined below, where our theoretical work is often done in direct collaboration with our experimental colleagues.
 
     
 

CRISPR/Cas modeling

CRISPR/Cas is a recently discovered adaptive bacterial immune system, which has found crucial biotechnology applications. Our modeling research focuses on the following question: How this normally silent system is induced, as even the virus infection in itself appears to be insufficient to activate the system. While it is hard to experimentally observe the system dynamics, this can be more readily done mathematically, where we use a combination of biophysical and dynamical system modeling.
 
 

CRISPR/Cas bioinformatics

Our CRISPR/Cas bioinformatics research focuses on non-canonical CRISPR/Cas functions. That is, while the system primary function is defense against foreign DNA, it is becoming increasingly clear that it also has important non-canonical functions, such as regulation of endogenous bacterial genes, which is mainly exhibited by small RNAs associated with CRISPR/Cas. As the system is active under poorly characterized conditions, CRISPR/Cas associated small RNAs can hardly be detected through RNA-seq. We develop bioinformatics methods that allow detecting these small RNAs directly from bacterial genome sequence. We also develop methods for predicting targets of these small RNAs, as these targets have up to now been completely unexplored.
 
 

Bioinformatics of transcription initiation under conditions of stress and stringency

Bacterial transcription is exhibited by alternative sigma factors under stress conditions, where their transcription initiation is generally poorly understood. We systematically study specificity of these alternative sigmas, where this analysis is aided by sequenced bacteriophage genomes, which encode a variety of different sigma factors. We use this analysis to reveal common mechanisms of bacterial transcription initiation, and to develop state-of-the-art methods for detection of transcription start-sites of diverse sigma factors.
 
 

Modeling restriction-modification (R-M) systems

R-M are rudimental bacterial immune systems, which are often spread by horizontal transfer. Consequently, expression of the restriction enzyme and the methylase has to be tightly regulated during its establishment in a naive bacterial host, which is often exhibited by specialized transcription regulators. These systems come with a variety of architectures (convergent, divergent, linear), where our main hypothesis is that these differences can be explained in terms of few general principles. Understanding these principles also allows constructing synthetic gene circuits where expression of molecules is tightly coordinated.
 
     
 
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