LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Cloning the λ Switch: Digital and Markov Representations of the Lambda Phage Infected E. coli Bacterium.

Photo from wikipedia

The lysis-lysogeny switch in E. coli due to infection from lambda phage has been extensively studied and explained by scientists of molecular biology. The bacterium either survives with the viral… Click to show full abstract

The lysis-lysogeny switch in E. coli due to infection from lambda phage has been extensively studied and explained by scientists of molecular biology. The bacterium either survives with the viral strand of Deoxyribonucleic acid (DNA), or dies producing hundreds of viruses for propagation of infection. Many proteins transcribed after infection by λ phage take part in determining the fate of the bacterium, but two proteins that play a key role in this regard are the cI and cro dimers, that are transcribed off the viral DNA. This paper presents a novel modeling mechanism for the lysis-lysogeny switch, by transferring the interactions of the main proteins, the lambda right operator and promoter regions and the Ribonucleic acid (RNA) polymerase, to a finite state machine (FSM), to determine cell fate. The FSM thus derived is implemented in field-programmable gate array (FPGA) and simulations have been run in random conditions. A Markov model has been created for the same mechanism. Steady state analysis has been conducted for the transition matrix of the Markov model and results have been generated to show the steady state probability of lysis with various model values. Through this work, it is hoped to lay down guidelines to convert biological processes into computing machines.

Keywords: cloning switch; bacterium; lambda phage; switch digital; phage; markov

Journal Title: IEEE transactions on nanobioscience
Year Published: 2019

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.