Computational systems medicine and disease control

Prof. Dr. Max von Kleist

October 07, 2022

Our group develops methods for computational systems medicine and computational systems biology and applies it to questions arising in fundamental science, infectious disease research and developmental processes. We welcome students with a bioinformatics and/or a mathematical biology/data science background who are excited about the research in these areas. Specifically, we are looking for a highly qualified student with a bioinformatics and/or a mathematical biology/data science background to work on:

Learning RNA structural ensembles from direct (nanopore) RNA sequencing of chemically probed molecules:

RNA is a functionally diverse molecule that is a central player in the regulation of many biological processes. More than a mere messenger, RNA molecules execute a vast array of crucial cellular functions. As such, RNA is increasingly recognized as a therapeutic target, therapeutic drug, and as a tool for synthetic biology. RNA function is based on its capacity to fold into intricate 3d structures formed from regions of single stranded and double stranded RNA. The resulting structural features are specifically recognized by proteins, small molecules, and other nucleic acids. This ability to bring together different components in time and space allows RNA to act as a scaffold and to regulate the biochemical activity of distinct molecular complexes within the cell. Axiomatic to RNA’s functional plasticity is structural heterogeneity. Rather than folding into a single structural conformation, RNA molecules can often adopt several different folds, each with a different function. Thus, the idea that RNA molecules fold into a single structural conformation with a given function has given way to one where RNA exists as a dynamic structural ensemble.

Experimentally, structural information can be derived by ‘chemical probing’1 of RNA molecules. The chemical probes selectively modify RNA-residues that are unpaired (‘free’ Watson-Crick edge). Following a ‘probing experiment’, chemical modifications can be detected by next generation sequencing, mapped onto the sequence and used for predicting RNA structure(s).

Within the domain of RNA structure-function inference, we intend to further our existing technical expertise1,2,3. In particular, we intend to develop computational (ML) methods to resolve RNA structural ensembles of the HIV-1 transcriptome in cells from high-throughput data provided by our experimental partners at the HIRI Würzburg that combine chemical probing1 with long-read nanopore direct RNA sequencing (dRNA-seq)5.  The project will involve aspects of bioinformatics, data science & statistics, as well as supervised and unsupervised machine learning. In particular, training of recurrent neural networks for nanopore base- and modification calling, as well as unsupervised methods for cluster detection (= structural conformations) in base-called read-ensembles will be the key to this project.


1General Principles for the Detection of Modified Nucleotides in RNA by Specific Reagents. M. Helm, …, Y. Motorin. Advanced Biology, 5, 2100866

2Mutational Interference Mapping Experiment (MIME) for studying the relationship between RNA structure and function. R.P. Smyth*, L. Despons, G. Huili, S. Bernacchi, M. Hijnen, J. Mak, F. Jossinet, L. Weixi, J-C. Paillart, M. von Kleist*, R. Marquet*, Nature Methods+, 12, 866 , 2015

3In cell Mutational Interference Mapping Experiment (in cell MIME) identifies 5’ PolyA as a dual regulator of HIV-1 genomic RNA production and packaging, R.P. Smyth*$, M.R. Smith$, A-C. Jousset, L. Despons, G. Laumond, T. Decoville, P. Cattenoz, C. Moog, F. Jossinet, M. Mougel, J.-C. Paillart, M. von Kleist*, R. Marquet*, Nucleic Acids Research, 46, e57, 2018

4Short and long-range interactions in the HIV-1 5'UTR regulate genome dimerization and Pr55Gag binding, L. Ye, ..., M. von Kleist, R.P. Smyth, Nature Struct & Mol Biol, 29, 306 2022

5Computational methods for RNA modification detection from nanopore direct RNA sequencing data. M. Furlan, …, T. Leonardi. RNA Biology, 18, 31, 2021


For more information visit the website of the Systems Pharmacology group.





© M. von Kleist


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