Stephanie Möllmert

Background: Atomic force microscopy (AFM) allows the mechanical characterization of single cells and live tissue by quantifying force-distance (FD) data in nano-indentation experiments. One of the main problems when dealing with biological tissue is the fact that the measured FD curves can be disturbed. These disturbances are caused, for instance, by passive cell movement, adhesive forces between the AFM probe and the cell, or insufficient attachment of the tissue to the supporting cover slide. In practice, the resulting artifacts are easily spotted by an experimenter who then manually sorts out curves before proceeding with data evaluation. However, this manual sorting step becomes increasingly cumbersome for studies that involve numerous measurements or for quantitative imaging based on FD maps.Results: We introduce the Python packagenanite, which automates all basic aspects of FD data analysis, including data import, tip-sample separation, base line correction, contact point retrieval, and model fitting. In addition,naniteenables the automation of the sorting step using supervised learning. This learning approach relates subjective ratings to predefined features extracted from FD curves. For ratings ranging from 0 to 10, our approach achieves a mean squared error below 1.0 rating points and a classification accuracy between good and poor curves that is above 87%. We showcase our approach by quantifying Young’s moduli of the zebrafish spinal cord at different classification thresholds and by introducing data quality as a new dimension for quantitative AFM image analysis.Conclusion: The addition of quality-based sorting using supervised learning enables a fully automated and reproducible FD data analysis pipeline for biological samples in AFM.

Many organisms, including yeast cells, bacteria, nematodes and tardigrades, endure harsh environmental conditions, such as nutrient scarcity, or lack of water and energy for a remarkably long time. The rescue programs that these organisms launch upon encountering these adverse conditions include reprogramming their metabolism in order to enter a quiescent or dormant state in a controlled fashion. Reprogramming coincides with changes in the macromolecular architecture and changes in the physical and mechanical properties of the cells. However, the cellular mechanisms underlying the physical-mechanical changes remain enigmatic. Here, we induce metabolic arrest of yeast cells by lowering their intracellular pH. We then determine the differences in the intracellular mass density and stiffness of active and metabolically arrested cells using optical diffraction tomography and atomic force microscopy. We show that an increased intracellular mass density is associated with an increase in stiffness when the growth of yeast is arrested. However, increasing the intracellular mass density alone is not sufficient for maintenance of the growth-arrested state in yeast cells. Our data suggest that the cytoplasm of metabolically arrested yeast displays characteristics of solid. Our findings constitute a bridge between the mechanical behavior of the cytoplasm and the physical and chemical mechanisms of metabolically arrested cells with the ultimate aim of understanding dormant organisms.

The mechanical properties of biological tissues are increasingly recognized as important factors in developmental and pathological processes. Most existing mechanical measurement techniques either necessitate destruction of the tissue for access or provide insufficient spatial resolution. Here, we show for the first time a systematic application of confocal Brillouin microscopy to quantitatively map the mechanical properties of spinal cord tissues during biologically relevant processes in a contact-free and non-destructive manner. Living zebrafish larvae were mechanically imaged in all anatomical planes, during development and after spinal cord injury. These experiments revealed that Brillouin microscopy is capable of detecting the mechanical properties of distinct anatomical structures without interfering with the animal’s natural development. The Brillouin shift within the spinal cord increased during development and transiently decreased during the repair processes following spinal cord transection. By taking into account the refractive index distribution, we explicitly determined the apparent longitudinal modulus and viscosity of different larval zebrafish tissues. Importantly, mechanical properties differed between tissues in situ and in excised slices. The presented work constitutes the first step towards an in vivo assessment of spinal cord tissue mechanics during regeneration, provides a methodical basis to identify key determinants of mechanical tissue properties and allows to test their relative importance in combination with biochemical and genetic factors during developmental and regenerative processes.