Dr. Martin Depken

Research Theme(s)Single-molecule biophysics, cell biology

Research Interestsgene editing, CRISPR-Cas, viral replication, single-molecule data-analysis methods, high-throughput data-analysis methods

 

Biography

Martin Depken is an associate professor in the Bionanosicence department at TU Delft. He received his D.Phil in theoretical physics from Oxford University in 2005, where he worked on exactly solvable models of low-dimensional non-equilibrium systems. He trained as a postdoc at the MPI-PKS/MPI-CBG in Dresden as well as at the University of Leiden and the Vrije Universiteit in Amsterdam. In 2011 he established the Theory of Molecular machines group at the BN department at TU Delft. Through bottom-up mechanistic modelling of the molecular machines that work the genetic code, the Depken group seeks to understand some of the most important structure-function relations in biology, health, and technology today. They work in close collaboration with experimenters to understand how anti-viral drugs influence viral replication machines like that of the SARS-CoV-2 virus, how the bacterial/archaeal defence systems CRISPR-Cas has been evolved to protect against viral invasions, how RNA guided nucleases find their targets, how the CRISPR-Cas system can be characterized and optimized for efficient and safe gene editing, and quantitative off-target prediction in gene editing applications. As of April 1st 2021, Martin is the Chair of the BN department at TU Delft.

 

For further information regarding current research and available projects, visit Depken lab.

Current Projects

CRISPR-Cas off-target prediction, the evolutionary arms race between CRISPR-Cas and viruses, target search on single-stranded substrates, viral replication

 

Highlight Publications

  • A mechanistic model improves off-target predictions and reveals the physical basis of SpCas9 fidelity
    B Eslami-Mossallam, M Klein, C v.d. Smagt, K v.d. Sanden, SK Jones Jr, JA Hawkins,  IJ Finkelstein, M Depken

https://www.biorxiv.org/content/10.1101/2020.05.21.108613v2

 

  • Fitting in the Age of Single-Molecule Experiments: A Guide to Maximum-Likelihood Estimation and Its Advantage
    B Eslami-Mosallam, I Katechis, M Depken
    Chapter in book: Biophysics of RNA-Protein Interactions, Springer, 2019
  • Hybridization kinetics explains CRISPR-Cas off-targeting rules
    M Klein, B Eslami-Mossallam, DG Arroyo, M Depken
    Cell reports 22 (6), 1413-1423, 2018
  • Crowding-induced transcriptional bursts dictate polymerase and nucleosome density profiles along genes
    AA van den Berg, M Depken
    Nucleic acids research 45 (13), 7623-7632, 2017
  • Elongation-competent pauses govern the fidelity of a viral RNA-dependent RNA polymerase
    D Dulin, ID Vilfan, BA Berghuis, S Hage, DH Bamford, MM Poranen, M Depken, NH Dekker
    Cell reports 10 (6), 983-992, 2015

 

 

Associate Professor

Martin Depken

Management Assistant

Valentina Luiten