Michael Jahn

We recently noticed problems to map next generation sequencing reads to certain regions of the Streptococcus genome, our pet organism for the study of pathogenic bacteria at the MPUSP. An extensive re-sequencing effort using short and long read methods revealed that the original assembly contained various errors, particularly for repetitive rRNA/tRNA operons (published now in MRA). Our new assembly fixes these errors and adds two new tRNAs, becoming the current reference assembly for Streptococcus pyogenes. It’s available on NCBI datasets.

We published our second paper about C.necator in AEM which uses a barcoded transposon library to study its energy metabolism. This is not only a continuation of our previous work but also a systematic survey in the spirit of the landmark paper by R. Cramm, 2008 – in this extensive review, the author meticulously collected all known information about the energy metabolism of this interesting organism. Our work investigated the relative importance of all formate dehydrogenases, hydrogenases, and electron transport chain complexes experimentally, with several remarkable findings. This study was a fruitful collaboration between three groups that I am sincerely grateful for, Paul Hudsons lab, Oliver Lenz’ lab, and Emmanuelle Charpentier’s lab.

Very happy that our newest CRISPRi library paper was finally published in The Plant Cell from Oxford University Press. The paper takes a deep dive into the subtle tradeoffs between growth rate and growth robustness in photosynthetic bacteria. All fitness data are available online in my R Shiny App ShinyLib.

Together with my colleagues at Science for Life Lab, Stockholm, we have submitted a new manuscript with the second iteration of our CRISPR interference library in cyanobacteria. The paper is currently in revision but can already be accessed on BioRxiv.org. It’s filled to brim with new insights about fitness tradeoffs in photosynthetic bacteria, such as fitness cost for the highly expressed photosystem and light harvesting protein machines. Special thanks to Rui Miao who is the shared first author with me.

I was recently invited to join the Editorial Board of the journal Frontiers in Bioengineering and Biotechnology. In the role of a review editor, I will occasionally review selected manuscripts for the journal and in return get public recognition for reviewing and editorial activities. This is more work for the me then for the journal, but it’s still an opportunity to be actively involved in the publishing process in my field. We will see how it goes.

New Job! After six exciting years as a Postdoc in Stockholm, I moved back to Germany together with my family. Living now in the greater Berlin area, I will start working at the Max Planck Unit for the Science of Pathogens (MPUSP) situated on the Charité campus in the heart of Berlin. I will work in the group of Emanuelle Charpentier, supporting different data-centered projects involving mass spectrometry, next generation sequencing, and many other things.

Cupriavidus necator Genome Scale Model We recently prepared a genome scale metabolic model for Ralstonia eutropha a.k.a. Cupriavidus necator H16. The model was previously published in Park et al., 2011, but no defined genome scale model definition was published with this paper, except from a PDF description. The original model in PDF format was later parsed and converted to SBML standard in a publication by Peyraud et al., PLoS Pathogens, 12(10), 2016, discovering a resource allocation trade-Off between virulence and proliferation in the plant pathogen Ralstonia solanacearum.

Purpose of RBA models The resource balance analysis (RBA) model is an extension of a standard genome scale model (GSM) where the solution space is constrained by many additional parameters. The topology of the metabolic network and its gene and reaction annotations are taken from the GSM. In a next step, enzymes and cellular ‘machineries’ are built based on data retrieved from uniprot. The model simulates all cellular processes from DNA replication, to transcription, translation and protein folding. The protein pool is limited so that the optimization of gene expression towards a specific objective (e.g. growth) becomes dependent on environmental parameters but also rate limitations. Catalytic efficiency of enzymes links enzyme abundance to maximal rate so that flux through the metabolic network can not become infinitely high.