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Institute of Bio- and Geosciences

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Research

Gene Regulation and Signal transduction


Most microorganisms are living in a complex and varying environment and, thus, must be able to rapidly adapt to changing conditions, such as nutrient availability, physical stresses or the presence of friends or foes. We are studying gene regulatory networks and signal transduction in the Gram-positive soil bacterium Corynebacterium glutamicum.

A current focus of our work is the interplay of two closely-related two-component systems (HrrSA and ChrSA) in heme-dependent gene expression. Interaction on multiple levels is required to optimally balance the use of heme as an alternative iron source, but at the same time avoid toxic intracellular levels thereof. Due to their unique properties, these systems represent an ideal model to study the early steps of pathway insulation in the evolution of TCS specificity.




Figure 1: The current model of HrrSA and ChrSA interaction in C. glutamcium. The ChrSA TCS predominantly mediates detoxification of heme by upregulation of hrtBA upon high heme levels. The HrrSA TCS is required for utilization of heme as an alternative source of iron by activating hmuO. Activation of the response regulators ChrA and HrrA is mediated by their cognate kinases ChrS and HrrS, but a cross-talk between non-cognate pairs was shown in this study. The kinases HrrS and ChrS have a dual function both as kinase and phosphatase. Phosphatase activity of each kinase was shown to be specific towards its cognate response regulator, thereby ensuring pathway specificity of these closely related systems.



Selected publications

  1. Hentschel, E., Gätgens, C., Bott, M., Brocker, M. & J. Frunzke*, (2014) Phosphatase activity of the histidine kinases ensures pathway specificity of the ChrSA and HrrSA two-component systems in Corynebacterium glutamicum. Mol Microbiol 92: 1326-42.
  2. Baumgart, M., K. Luder, S. Grover, C. Gätgens, G. S. Besra & J. Frunzke*, (2013) IpsA, a novel LacI-type regulator, is required for inositol-derived lipid formation in Corynebacteria and Mycobacteria. BMC Biol 11: 122.
  3. Francez-Charlot, A. 1, J. Frunzke1, C. Reichen, J. Z. Ebneter, B. Gourion & J. A. Vorholt, (2009) Sigma factor mimicry involved in regulation of general stress response. Proc Natl Acad Sci USA 106: 3467-3472.

Transcription factor-based biosensors


Living organisms have evolved a plethora of sensing systems for the intra- and extracellular detection of small molecules, ions and physical parameters. We exploit and incorporate these sensory mechanisms in synthetic circuits to devise genetically-encoded biosensors, which are highly valuable for a wide range of biotechnological applications.

We are particular interested in developing and applying transcriptional regulator-based biosensors, which transfer cellular metabolite production into an easily detectable and measureable output (e.g. fluorescence). These sensors proved highly efficient to screen large mutant libraries for variants with increased metabolite production in a high-throughput manner using fluorescence-activated cell sorting (FACS). In a recent study, we successfully established a biosensor-driven adaptive laboratory evolution strategy, which proved efficient to increase metabolite production by iteratively imposing an artificial selective pressure on the fluorescent output of the biosensor using FACS.

In addition, biosensors enable us to monitor bioprocesses at the single cell level via flow cytometric (FC) analysis or via live cell imaging studies in microfluidic chip devices. This presents the key for identifying and studying metabolic heterogeneity in bioprocesses, which is of high interest for biotechnological process improvement.


Versatile application of genetically-encoded biosensors

Figure 2: Versatile application of genetically-encoded biosensors. Biosensors with an optical readout, e.g. production of an autofluorescent protein (AFP), are efficient tools for the high-throughput screening of large mutant libraries using FACS. Biosensor-driven evolution has proven a convenient strategy to increase production by iteratively imposing an artificial



Selected publications

  1. Mahr, R., and J. Frunzke*, (2016) Transcription factor-based biosensors in biotechnology: current state and future prospects. Appl Microbiol Biotechnol 100:79-90. doi: 10.1007/s00253-015-7090-3
  2. Mahr, R., C. Gätgens, J. Gätgens, T. Polen, J. Kalinowski, and J. Frunzke*, (2015) Biosensor-driven adaptive laboratory evolution of l-valine production in Corynebacterium glutamicum. Metab Eng 32:184-194. doi: 10.1016/j.ymben.2015.09.017
  3. Mustafi, N., A. Grünberger, R. Mahr, S. Helfrich, K. Nöh, B. Blombach, D. Kohlheyer & J. Frunzke*, (2014) Application of a Genetically Encoded Biosensor for Live Cell Imaging of L-Valine Production in Pyruvate Dehydrogenase Complex-Deficient Corynebacterium glutamicum Strains. PLoS One 9: e85731.
  4. Mustafi, N., A. Grünberger, D. Kohlheyer, M. Bott & J. Frunzke*, (2012) The development and application of a single-cell biosensor for the detection of L-methionine and branched-chain amino acids. Metab Eng 14: 449-457.

Microbial Population Dynamics


Microbial populations and communities typically display a highly dynamic behavior which enables them to adapt and interact with their particular environmental niche and to communicate with other species. These dynamic changes include the spontaneous arise of mutations, genomic rearrangements or the activation of mobile genomic elements such as prophages (see below), but also goes beyond this level to the level of phenotypic heterogeneity. This variability occurs independently of external conditions and manifests even between genetically identical cells living in the same microenvironment.

In our laboratory uses state-of-the-art single-cell approaches to study the phenotypic structure of bacterial populations with respect to various parameters. Protocols have been established, to monitor DNA content, membrane potential, membrane integrity (viability) or metabolite production (see, transcription factor-based biosensors) at the single cell level using flow cytometry. Here, we work in close cooperation with the group of Dr. Kohlheyer (IBG-1, FZJ) who is developing microfluidic devices to grow microbial populations under well-defined conditions.

Prophage-host interaction


Temperate bacteriophages are able to integrate into the host genome and maintain as prophages a long-term association with their host. These prophages represent a ubiquitous element of bacterial genomes. Illustrated by the development of mutually beneficial traits, this close interaction between host and virus has significantly shaped bacterial evolution. However, the immense genetic resources of phage genomes still remain almost unexplored.

We are in particular interested in the spontaneous induction of prophage elements (SPI), which occurs even in the absence of an external stimulus – under non-inducing conditions. Originally, this spontaneous prophage induction was considered to be a potentially detrimental process, but recent research in the field of microbial biofilms, host-pathogen interaction and population dynamics emphasizes that SPI is an important contributor to the social behaviour of microbes. We are studying the molecular factors influencing SPI in single individuals, and also how the host modulates its frequency.



Spontaneous induction of the CGP3 prophage


Figure 3: Spontaneous induction of the CGP3 prophage monitored by live cell imaging of isogenic microcolonies of C. glutamicum (yellow: SOS response; red: prophage induction). Data can be visualized by fluorescent traces of single cells (left graph) or as lineage trees of selected microcolonies (right graph).


Selected publications

  1. Pfeifer E., Hünnefeld M., Popa O., Polen T., Kohlheyer D., M. Baumgart and J. Frunzke* (2016) Silencing of cryptic prophages in Corynebacterium glutamicum. Nucleic Acids Res, doi: 10.1093/nar/gkw692
  2. Helfrich, S., E. Pfeifer, C. Krämer, C. C. Sachs, W. Wiechert, D. Kohlheyer, K. Nöh*, and J. Frunzke*, (2015) Live cell imaging of SOS and prophage dynamics in isogenic bacterial populations. Mol Microbiol 98:636-650. doi: 10.1111/mmi.13147
  3. Nanda, A. M., Thormann, K., and Frunzke, J.*, (2015) Impact of spontaneous prophage induction on the fitness of bacterial populations and host-microbe interactions. J Bacteriol 197: 410-419

Methodology and Lab equipment


Students in our laboratory can expect to gain experience in several interesting and modern techniques and methods, including:

  • Molecular microbiology: standard cloning techniques, site-directed mutagenesis, Gibson assembly
  • Single-cell analysis: Time-laps fluorescence microscopy (Live Cell Imaging), flow cytometry and cell sorting (FACS)
  • OMICS techniques: in particular transcriptomics (microarrays & RNA-Seq) and proteomics
  • Next-generation sequencing: Genome re-sequencing and RNA-Seq (Illumina, MiSeq)

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