RNA Kinetics and Co-transcriptional Folding

The folding of RNA is a kinetic process which depends on the formation of Watson-Crick basepairs between pairs of nucleotides. A kinetic trajectory can be solved using a Gillespie stochastic algorithm, where the RNA adds/deletes single base-pairs over time. However, the computational cost per base-pair addition/deletion scales as O(n) with the sequence length n. My work on KFOLD focused on developing a faster computational technique for RNA kinetics that allows simulation of an exact Gillepspie RNA folding trajectory that scales logarithmically with sequence size.

Example trajectories, computed using KFOLD, can be seen below. For further details see:
Dykeman E.C. (2015)
An implementation of the Gillespie algorithm for RNA kinetics with logarithmic time update.
Nucleic Acids Research 43, 5708-5715.

In vivo Models of Ribosome Kinetics

In vivo , ribosomes interact with the full transcriptome of the cell, i.e. the complete set of mRNAs which have been transcribed by the cell. These mRNAs interact with thousands of ribosomes to produce the proteins needed in a cell. The complex interplay between all the proteins needed for the elongation process (such as tRNAs and elongation factors) give rise to a complicated systems dynamics of the translation process. Using a full description of all of the reactions important for ribosome elongation has resulted in a number of experimental observations, such as the increasing peptide elongation rate with increasing bacterial growth rate (shown below), to be reproduced.

For further details see:
Dykeman E.C. (2019)
A stochastic model of in vivo ribosome kinetics.

Viral Assembly Models

During infection of a host cell, ss-RNA viruses must selectively package their own genetic material in competition with numerous host mRNAs which are present in the cell. RNA-protein interactions are believed to play a crucial role in the selective packaging of viral mRNAs over cellular mRNAs. Incorporation of PS mediated assembly in a model of a cellular viral infection has demonstrated how specialised RNA sites within the viral RNA called packaging signals (PSs) can result in a scenario where viral RNAs are selectively packaged over cellular mRNA competitors.

Example trajectories, with PSs present in the viral RNA and the effects of drugs which target them, can be seen below. For further details see:
Dykeman E.C., Stockley P.G., Twarock R. (2014)
Solving a Levinthal's paradox for virus assembly identifies a unique antiviral strategy.
Proc. Nat. Acad. of Sciences USA 111, 5361-5366.

I have extended this viral assembly model to include explicit RNA nucleotide sequences which have the capability of encoding a gene product. These sequences, once evolved, were able to outcompete other RNA sequences with lower fitness and allowed for a description of a sequence fitness landscape. For further details see:
Dykeman E.C. (2017)
A Model for Viral Assembly around an Explicit RNA Sequence Generates an Implicit Fitness Landscape.
Biophysical Journal 113, 506-516.

Intracellular Models of Viral Infection

Viruses hijack the cellular machinery, in particular the host cells ribosomes, to preferentially direct the cell to produce viral proteins and components needed to make progeny virus. The regulation of the amount of each viral protein and the time point during the infection in which it is produced, is crucial for a sucessful viral infection of the cell. Many ssRNA viruses, such as MS2, have solved this timing and regulation issue by using translational couplings and secondary structures in the RNA to control access of cellular ribosomes to viral genes. I am currently working on a model which combines my Ribosome kinetics model with RNA folding to examine the processes that viruses like MS2 utilize to regulate the production of their viral proteins.