Welcome to the website of Biological Optomechanics Division
Cells are the basic entities of biological systems. They have particular physical properties, which enable them to navigate their 3D physical environment and fulfill their biological functions. We investigate these physical – mechanical and optical – properties of living cells and tissues using novel photonics and biophysical tools to test their biological importance. Our ultimate goal is the transfer of our findings to medical application in the fields of improved diagnosis of diseases and novel approaches in regenerative medicine.
Mechanical properties of cells are very often connected to their state and function. They can thus serve as an intrinsic biophysical marker of cell state transitions, such as metastasis of cancer cells, activation of leukocytes, or progression through the cell cycle. Read More...
Cells actively sense and respond to a variety of mechanical signals — a process known as mechanosensing. Mechanical cues provided by the extracellular environment can modulate a wide spectrum of cellular events, including cell proliferation, differentiation and protein production. Read More...
Cells define and largely form their surrounding tissues and, in return, receive biochemical and physical cues from them. We are working on resolving this interdependence by quantifying these tissue mechanical properties, correlating them with biological function, investigating their origin and ultimately controlling them. Read More...
Biophotonics describes the interaction of light with cells and tissues. We are interested in the interaction between light and tissues which is governed by the optical properties of cells. Read More...
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Embracing the diversity of model systems to deconstruct the basis
of regeneration and tissue repair
The eighth EMBO conference in the series ‘The Molecular and Cellular Basis of Regeneration and Tissue Repair’ took place in Barcelona (Spain) in September 2022. A total of 173 researchers from across the globe shared their latest advances in deciphering the molecular and cellular basis of wound healing, tissue repair and<br>regeneration, as well as their implications for future clinical applications. The conference showcased an ever-expanding diversity of model organisms used to identify mechanisms that promote regeneration. Over 25 species were discussed, ranging from invertebrates to humans. Here, we provide an overview of the exciting topics presented at the conference, highlighting novel discoveries in regeneration and perspectives for regenerative medicine.
Image-based cell sorting using focused travelling surface acoustic waves
Sorting cells is an essential primary step in many biological and clinical applications such as high-throughput drug screening, cancer research and cell transplantation. Cell sorting based on their mechanical properties has long been considered as a promising label-free biomarker that could revolutionize the isolation of cells from heterogeneous populations. Recent advances in microfluidic image-based cell analysis combined with subsequent label-free sorting by on-chip actuators demonstrated the possibility of sorting cells based on their physical properties. However, the high purity of sorting is achieved at the expense of a sorting rate that lags behind the analysis throughput. Furthermore, stable and reliable system operation is an important feature in enabling the sorting of small cell fractions from a concentrated heterogeneous population. Here, we present a label-free cell sorting method, based on the use of focused travelling surface acoustic wave (FTSAW) in combination with real-time deformability cytometry (RT-DC). We demonstrate the flexibility and applicability of the method by sorting distinct blood cell types, cell lines and particles based on different physical parameters. Finally, we present a new strategy to sort cells based on their mechanical properties. Our system enables the sorting of up to 400 particles per s. Sorting is therefore possible at high cell concentrations (up to 36 million per ml) while retaining high purity (>92%) for cells with diverse sizes and mechanical properties moving in a highly viscous buffer. Sorting of small cell fraction from a heterogeneous population prepared by processing of small sample volume (10 μl) is also possible and here demonstrated by the 667-fold enrichment of white blood cells (WBCs) from raw diluted whole blood in a continuous 10-hour sorting experiment. The real-time analysis of multiple parameters together with the high sensitivity and high-throughput of our method thus enables new biological and therapeutic applications in the future.
Evolutionary rescue of resistant mutants is governed by a balance between radial expansion and selection in compact populations
Serhii Aif, Nico Appold, Lucas Kampman, Oskar Hallatschek, Jona Kayser
Mutation-mediated treatment resistance is one of the primary challenges for modern antibiotic and anti-cancer therapy. Yet, many resistance mutations have a substantial fitness cost and are subject to purifying selection. How emerging resistant lineages may escape purifying selection via subsequent compensatory mutations is still unclear due to the difficulty of tracking such evolutionary rescue dynamics in space and time. Here, we introduce a system of fluorescence-coupled synthetic mutations to show that the probability of evolutionary rescue, and the resulting long-term persistence of drug resistant mutant lineages, is dramatically increased in dense microbial populations. By tracking the entire evolutionary trajectory of thousands of resistant lineages in expanding yeast colonies we uncover an underlying quasi-stable equilibrium between the opposing forces of radial expansion and natural selection, a phenomenon we term inflation-selection balance. Tailored computational models and agent-based simulations corroborate the fundamental nature of the observed effects and demonstrate the potential impact on drug resistance evolution in cancer. The described phenomena should be considered when predicting multi-step evolutionary dynamics in any mechanically compact cellular population, including pathogenic microbial biofilms and solid tumors. The insights gained will be especially valuable for the quantitative understanding of response to treatment, including emerging evolution-based therapy strategies.
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