Estimation of the mass density of biological matter from refractive index measurements.

The quantification of physical properties of biological matter gives rise to novel ways of understanding functional mechanisms. One of the basic biophysical properties is the mass density (MD). It affects the dynamics in sub-cellular compartments and plays a major role in defining the opto-acoustical properties of cells and tissues. As such, the MD can be connected to the refractive index (RI) via the well known Lorentz-Lorenz relation, which takes into account the polarizability of matter. However, computing the MD based on RI measurements poses a challenge, as it requires detailed knowledge of the biochemical composition of the sample. Here we propose a methodology on how to account for assumptions about the biochemical composition of the sample and respective RI measurements. To this aim, we employ the Biot mixing rule of RIs alongside the assumption of volume additivity to find an approximate relation of MD and RI. We use Monte-Carlo simulations and Gaussian propagation of uncertainty to obtain approximate analytical solutions for the respective uncertainties of MD and RI. We validate this approach by applying it to a set of well-characterized complex mixtures given by bovine milk and intralipid emulsion and employ it to estimate the MD of living zebrafish (Danio rerio) larvae trunk tissue. Our results illustrate the importance of implementing this methodology not only for MD estimations but for many other related biophysical problems, such as mechanical measurements using Brillouin microscopy and transient optical coherence elastography.

Small leucine-rich proteoglycans inhibit CNS regeneration by modifying the structural and mechanical properties of the lesion environment.

Extracellular matrix (ECM) deposition after central nervous system (CNS) injury leads to inhibitory scarring in humans and other mammals, whereas it facilitates axon regeneration in the zebrafish. However, the molecular basis of these different fates is not understood. Here, we identify small leucine-rich proteoglycans (SLRPs) as a contributing factor to regeneration failure in mammals. We demonstrate that the SLRPs chondroadherin, fibromodulin, lumican, and prolargin are enriched in rodent and human but not zebrafish CNS lesions. Targeting SLRPs to the zebrafish injury ECM inhibits axon regeneration and functional recovery. Mechanistically, we find that SLRPs confer mechano-structural properties to the lesion environment that are adverse to axon growth. Our study reveals SLRPs as inhibitory ECM factors that impair axon regeneration by modifying tissue mechanics and structure, and identifies their enrichment as a feature of human brain and spinal cord lesions. These findings imply that SLRPs may be targets for therapeutic strategies to promote CNS regeneration.

Unbiased retrieval of frequency-dependent mechanical properties from noisy time-dependent signals.

The mechanical response of materials to dynamic loading is often quantified by the frequency-dependent complex modulus. Probing materials directly in the frequency domain faces technical challenges such as a limited range of frequencies, long measurement times, or small sample sizes. Furthermore, many biological samples, such as cells or tissues, can change their properties upon repetitive probing at different frequencies. Therefore, it is common practice to extract the material properties by fitting predefined mechanical models to measurements performed in the time domain. This practice, however, precludes the probing of unique and yet unexplored material properties. In this report, we demonstrate that the frequency-dependent complex modulus can be robustly retrieved in a model-independent manner directly from time-dependent stress-strain measurements. While applying a rolling average eliminates random noise and leads to a reliable complex modulus in the lower frequency range, a Fourier transform with a complex frequency helps to recover the material properties at high frequencies. Finally, by properly designing the probing procedure, the recovery of reliable mechanical properties can be extended to an even wider frequency range. Our approach can be used with many state-of-the-art experimental methods to interrogate the mechanical properties of biological and other complex materials.

Viscoelastic properties of suspended cells measured with shear flow deformation cytometry.

Numerous cell functions are accompanied by phenotypic changes in viscoelastic properties, and measuring them can help elucidate higher level cellular functions in health and disease. We present a high-throughput, simple and low-cost microfluidic method for quantitatively measuring the elastic (storage) and viscous (loss) modulus of individual cells. Cells are suspended in a high-viscosity fluid and are pumped with high pressure through a 5.8 cm long and 200 µm wide microfluidic channel. The fluid shear stress induces large, ear ellipsoidal cell deformations. In addition, the flow profile in the channel causes the cells to rotate in a tank-treading manner. From the cell deformation and tank treading frequency, we extract the frequency-dependent viscoelastic cell properties based on a theoretical framework developed by R. Roscoe [1] that describes the deformation of a viscoelastic sphere in a viscous fluid under steady laminar flow. We confirm the accuracy of the method using atomic force microscopy-calibrated polyacrylamide beads and cells. Our measurements demonstrate that suspended cells exhibit power-law, soft glassy rheological behavior that is cell-cycle-dependent and mediated by the physical interplay between the actin filament and intermediate filament networks.

Cells in the human body are viscoelastic: they have some of the properties of an elastic solid, like rubber, as well as properties of a viscous fluid, like oil. To carry out mechanical tasks ­ such as, migrating through tissues to heal a wound or to fight inflammation ­ cells need the right balance of viscosity and elasticity. Measuring these two properties can therefore help researchers to understand important cell tasks and how they are impacted by disease. However, quantifying these viscous and elastic properties is tricky, as both depend on the time-scale they are measured: when pressed slowly, cells appear soft and liquid, but they turn hard and thick when rapidly pressed. Here, Gerum et al. have developed a new system for measuring the viscosity and elasticity of individual cells that is fast, simple, and inexpensive. In this new method, cells are suspended in a specialized solution with a consistency similar to machine oil which is then pushed with high pressure through channels less than half a millimeter wide. The resulting flow of fluid shears the cells, causing them to elongate and rotate, which is captured using a fast camera that takes 500 images per second. Gerum et al. then used artificial intelligence to extract each cell's shape and rotation speed from these images, and calculated their viscosity and elasticity based on existing theories of how viscoelastic objects behave in fluids. Gerum et al. also investigated how the elasticity and viscosity of cells changed with higher rotation frequencies, which corresponds to shorter time-scales. This revealed that while higher frequencies made the cells appear more viscous and elastic, the ratio between these two properties remained the same. This means that researchers can compare results obtained from different experimental techniques, even if the measurements were carried out at completely different frequencies or time-scales. The method developed by Gerum et al. provides a fast an inexpensive way for analyzing the viscosity and elasticity of cells. It could also be a useful tool for screening the effects of drugs, or as a diagnostic tool to detect diseases that affect the mechanical properties of cells.

Pressure and curvature control of the cell cycle in epithelia growing under spherical confinement.

Morphogenesis requires spatiotemporal regulation of proliferation, both by biochemical and mechanical cues. In epithelia, this regulation is called contact inhibition of proliferation, but disentangling biochemical from mechanical cues remains challenging. Here, we show that epithelia growing under confinement accumulate pressure that inhibits proliferation above a threshold value. During growth, epithelia spontaneously buckle, and cell proliferation is transiently reactivated within the fold. Reactivation of proliferation within folds correlated with the local reactivation of the mechano-sensing YAP/TAZ pathway. At late time points, when the pressure is highest, ß-catenin activity increases. The threshold pressure increases when ß-catenin is overactivated and decreases when ß-catenin is inhibited. Altogether, our results suggest that different mechanical cues resulting from pressure inhibition of proliferation are at play through different mechano-sensing pathways: the ß-catenin pathway sustains cell division under high pressure, and the YAP pathway senses local curvature.

Adipose cells and tissues soften with lipid accumulation while in diabetes adipose tissue stiffens.

Adipose tissue expansion involves both differentiation of new precursors and size increase of mature adipocytes. While the two processes are well balanced in healthy tissues, obesity and diabetes type II are associated with abnormally enlarged adipocytes and excess lipid accumulation. Previous studies suggested a link between cell stiffness, volume and stem cell differentiation, although in the context of preadipocytes, there have been contradictory results regarding stiffness changes with differentiation. Thus, we set out to quantitatively monitor adipocyte shape and size changes with differentiation and lipid accumulation. We quantified by optical diffraction tomography that differentiating preadipocytes increased their volumes drastically. Atomic force microscopy (AFM)-indentation and -microrheology revealed that during the early phase of differentiation, human preadipocytes became more compliant and more fluid-like, concomitant with ROCK-mediated F-actin remodelling. Adipocytes that had accumulated large lipid droplets were more compliant, and further promoting lipid accumulation led to an even more compliant phenotype. In line with that, high fat diet-induced obesity was associated with more compliant adipose tissue compared to lean animals, both for drosophila fat bodies and murine gonadal adipose tissue. In contrast, adipose tissue of diabetic mice became significantly stiffer as shown not only by AFM but also magnetic resonance elastography. Altogether, we dissect relative contributions of the cytoskeleton and lipid droplets to cell and tissue mechanical changes across different functional states, such as differentiation, nutritional state and disease. Our work therefore sets the basis for future explorations on how tissue mechanical changes influence the behaviour of mechanosensitive tissue-resident cells in metabolic disorders.

An explicit model to extract viscoelastic properties of cells from AFM force-indentation curves.

Atomic force microscopy (AFM) is widely used for quantifying the mechanical properties of soft materials such as cells. AFM force-indentation curves are conventionally fitted with a Hertzian model to extract elastic properties. These properties solely are, however, insufficient to describe the mechanical properties of cells. Here, we expand the analysis capabilities to describe the viscoelastic behavior while using the same force-indentation curves. Our model gives an explicit relation of force and indentation and extracts physically meaningful mechanical parameters. We first validated the model on simulated force-indentation curves. Then, we applied the fitting model to the force-indentation curves of two hydrogels with different crosslinking mechanisms. Finally, we characterized HeLa cells in two cell cycle phases, interphase and mitosis, and showed that mitotic cells have a higher apparent elasticity and a lower apparent viscosity. Our study provides a simple method, which can be directly integrated into the standard AFM framework for extracting the viscoelastic properties of materials.

Correlative all-optical quantification of mass density and mechanics of subcellular compartments with fluorescence specificity.

Quantitative measurements of physical parameters become increasingly important for understanding biological processes. Brillouin microscopy (BM) has recently emerged as one technique providing the 3D distribution of viscoelastic properties inside biological samples - so far relying on the implicit assumption that refractive index (RI) and density can be neglected. Here, we present a novel method (FOB microscopy) combining BM with optical diffraction tomography and epifluorescence imaging for explicitly measuring the Brillouin shift, RI, and absolute density with specificity to fluorescently labeled structures. We show that neglecting the RI and density might lead to erroneous conclusions. Investigating the nucleoplasm of wild-type HeLa cells, we find that it has lower density but higher longitudinal modulus than the cytoplasm. Thus, the longitudinal modulus is not merely sensitive to the water content of the sample - a postulate vividly discussed in the field. We demonstrate the further utility of FOB on various biological systems including adipocytes and intracellular membraneless compartments. FOB microscopy can provide unexpected scientific discoveries and shed quantitative light on processes such as phase separation and transition inside living cells.

AIDeveloper: Deep Learning Image Classification in Life Science and Beyond.

Artificial intelligence (AI)-based image analysis has increased drastically in recent years. However, all applications use individual solutions, highly specialized for a particular task. Here, an easy-to-use, adaptable, and open source software, called AIDeveloper (AID) to train neural nets (NN) for image classification without the need for programming is presented. AID provides a variety of NN-architectures, allowing to apply trained models on new data, obtain performance metrics, and export final models to different formats. AID is benchmarked on large image datasets (CIFAR-10 and Fashion-MNIST). Furthermore, models are trained to distinguish areas of differentiated stem cells in images of cell culture. A conventional blood cell count and a blood count obtained using an NN are compared, trained on >1.2 million images, and demonstrated how AID can be used for label-free classification of B- and T-cells. All models are generated by non-programmers on generic computers, allowing for an interdisciplinary use.

Compliant Substrates Enhance Macrophage Cytokine Release and NLRP3 Inflammasome Formation During Their Pro-Inflammatory Response.

Immune cells process a myriad of biochemical signals but their function and behavior are also determined by mechanical cues. Macrophages are no exception to this. Being present in all types of tissues, macrophages are exposed to environments of varying stiffness, which can be further altered under pathological conditions. While it is becoming increasingly clear that macrophages are mechanosensitive, it remains poorly understood how mechanical cues modulate their inflammatory response. Here we report that substrate stiffness influences the expression of pro-inflammatory genes and the formation of the NLRP3 inflammasome, leading to changes in the secreted protein levels of the cytokines IL-1ß and IL-6. Using polyacrylamide hydrogels of tunable elastic moduli between 0.2 and 33.1 kPa, we found that bone marrow-derived macrophages adopted a less spread and rounder morphology on compliant compared to stiff substrates. Upon LPS priming, the expression levels of the gene encoding for TNF-α were higher on more compliant hydrogels. When additionally stimulating macrophages with the ionophore nigericin, we observed an enhanced formation of the NLRP3 inflammasome, increased levels of cell death, and higher secreted protein levels of IL-1ß and IL-6 on compliant substrates. The upregulation of inflammasome formation on compliant substrates was not primarily attributed to the decreased cell spreading, since spatially confining cells on micropatterns led to a reduction of inflammasome-positive cells compared to well-spread cells. Finally, interfering with actomyosin contractility diminished the differences in inflammasome formation between compliant and stiff substrates. In summary, we show that substrate stiffness modulates the pro-inflammatory response of macrophages, that the NLRP3 inflammasome is one of the components affected by macrophage mechanosensing, and a role for actomyosin contractility in this mechanosensory response. Thus, our results contribute to a better understanding of how microenvironment stiffness affects macrophage behavior, which might be relevant in diseases where tissue stiffness is altered and might potentially provide a basis for new strategies to modulate inflammatory responses.

Buckling of an Epithelium Growing under Spherical Confinement.

Many organs are formed through folding of an epithelium. This change in shape is usually attributed to tissue heterogeneities, for example, local apical contraction. In contrast, compressive stresses have been proposed to fold a homogeneous epithelium by buckling. While buckling is an appealing mechanism, demonstrating that it underlies folding requires measurement of the stress field and the material properties of the tissue, which are currently inaccessible in vivo. Here, we show that monolayers of identical cells proliferating on the inner surface of elastic spherical shells can spontaneously fold. By measuring the elastic deformation of the shell, we infer the forces acting within the monolayer and its elastic modulus. Using analytical and numerical theories linking forces to shape, we find that buckling quantitatively accounts for the shape changes of our monolayers. Our study shows that forces arising from epithelial growth in three-dimensional confinement are sufficient to drive folding by buckling.

Intelligent image-based deformation-assisted cell sorting with molecular specificity.

Although label-free cell sorting is desirable for providing pristine cells for further analysis or use, current approaches lack molecular specificity and speed. Here, we combine real-time fluorescence and deformability cytometry with sorting based on standing surface acoustic waves and transfer molecular specificity to image-based sorting using an efficient deep neural network. In addition to general performance, we demonstrate the utility of this method by sorting neutrophils from whole blood without labels.

Zebrafish Spinal Cord Repair Is Accompanied by Transient Tissue Stiffening.

Severe injury to the mammalian spinal cord results in permanent loss of function due to the formation of a glial-fibrotic scar. Both the chemical composition and the mechanical properties of the scar tissue have been implicated to inhibit neuronal regrowth and functional recovery. By contrast, adult zebrafish are able to repair spinal cord tissue and restore motor function after complete spinal cord transection owing to a complex cellular response that includes axon regrowth and is accompanied by neurogenesis. The mechanical mechanisms contributing to successful spinal cord repair in adult zebrafish are, however, currently unknown. Here, we employ atomic force microscopy-enabled nanoindentation to determine the spatial distributions of apparent elastic moduli of living spinal cord tissue sections obtained from uninjured zebrafish and at distinct time points after complete spinal cord transection. In uninjured specimens, spinal gray matter regions were stiffer than white matter regions. During regeneration after transection, the spinal cord tissues displayed a significant increase of the respective apparent elastic moduli that transiently obliterated the mechanical difference between the two types of matter before returning to baseline values after the completion of repair. Tissue stiffness correlated variably with cell number density, oligodendrocyte interconnectivity, axonal orientation, and vascularization. This work constitutes the first quantitative mapping of the spatiotemporal changes of spinal cord tissue stiffness in regenerating adult zebrafish and provides the tissue mechanical basis for future studies into the role of mechanosensing in spinal cord repair.

nanite: using machine learning to assess the quality of atomic force microscopy-enabled nano-indentation data.

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 package nanite, 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, nanite enables 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.

Mechanical Mapping of Spinal Cord Growth and Repair in Living Zebrafish Larvae by Brillouin Imaging.

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 to our knowledge 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 nondestructive 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 remained comparable during development and transiently decreased during the repair processes after 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 toward 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 us to test their relative importance in combination with biochemical and genetic factors during developmental and regenerative processes.

Single-cell mechanical phenotype is an intrinsic marker of reprogramming and differentiation along the mouse neural lineage.

Cellular reprogramming is a dedifferentiation process during which cells continuously undergo phenotypical remodeling. Although the genetic and biochemical details of this remodeling are fairly well understood, little is known about the change in cell mechanical properties during the process. In this study, we investigated changes in the mechanical phenotype of murine fetal neural progenitor cells (fNPCs) during reprogramming to induced pluripotent stem cells (iPSCs). We find that fNPCs become progressively stiffer en route to pluripotency, and that this stiffening is mirrored by iPSCs becoming more compliant during differentiation towards the neural lineage. Furthermore, we show that the mechanical phenotype of iPSCs is comparable with that of embryonic stem cells. These results suggest that mechanical properties of cells are inherent to their developmental stage. They also reveal that pluripotent cells can differentiate towards a more compliant phenotype, which challenges the view that pluripotent stem cells are less stiff than any cells more advanced developmentally. Finally, our study indicates that the cell mechanical phenotype might be utilized as an inherent biophysical marker of pluripotent stem cells.

Asymmetry in traction forces produced by migrating preadipocytes is bounded to 33.

Wound healing by gap closure is accomplished by the migratory cells within tissues. In fat tissue, the preadipocytes, stem cells committed to the adipose (fat) lineage, typically migrate into the wound area, and then differentiate into mature adipocytes to facilitate tissue repair and regeneration. While cell migration has previously been characterized, typically for fibroblasts, little is known about the dynamic, mechanical interactions of migrating cells with their microenvironment; cells crawl on a two-dimensional (2D) substrate by attaching and applying forces that allow them to extend leading edges and retract their rear. Moreover, preadipocytes, the highly migratory precursors of fat cells, have not been studied from this aspect. Here, we have evaluated the migration of preadipocytes, through their speed and directionality as well as the magnitude of the lateral forces applied during their migration on a 2D gel with Young's modulus of 2.44 kPa. We have found that the preadipocytes migrate non-directionally in the absence of chemoattractant, at an average rate of 0.27 µm/min, similar to fibroblasts. The preadipocytes exhibited a wide range of total traction forces (100-800 nN), and migrated along the long axis of their elongated morphology. Interestingly, we have observed an asymmetry in the location of force application between the lead and rear of the cells that was bounded in magnitude, where cells applied only up to 33% more force on either side; cell sides were defined relative to the minor axis of a bounding ellipse. These quantitative mechanobiological aspects of natural preadipocyte migration may shed light on the wound healing processes occurring in adipose tissue.

Ratio of total traction force to projected cell area is preserved in differentiating adipocytes.

During obesity development, preadipocytes proliferate and differentiate into new mature adipocytes, to increase the storage capacity of triglycerides. The morphology of the cells changes during differentiation from an elongated spindle-shape preadipocyte into a rounded, differentiated adipocyte. That change allows efficient packing of spheroidal (triglyceride) lipid droplets in the cells, also reducing their ability to proliferate and migrate. The change in preadipocyte morphology is well known. However, little is known about the dynamic mechanical interactions of the cells with their microenvironment, and specifically the forces applied by the cells during and following differentiation. In this study, we evaluated changes in the morphology concurrently with the magnitude and location of forces applied by the cells onto a compliant gel-substrate. We found that the elongated preadipocytes applied forces concentrated at the poles of the cell, yet during differentiation the forces become more uniformly distributed around the cell and mostly at its perimeter. Furthermore, we observed that the total traction force per cell area is preserved, remaining essentially unchanged between preadipocytes and differentiated cells 3-14 days post-differentiation. At differentiation times longer than 8 days we also observed an increasing subset of cells that indent the gels, as opposed to merely applying horizontal traction forces. Our work provides insights into the dynamic mechanobiology of the adipogenesis process.