Biology subjects

Abuhattum, S.

Publications and source records attributed to Abuhattum, S..

12 recordsLinked to original sources

bioRxiv2023

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 by utilizing models that explicitly depend on physical observables. One of the basic biophysical properties is the mass density (MD), which determines the degree of crowdedness. It impacts the dynamics in sub-cellular compartments and further 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 a priori and a posteriori assumptions about the biochemical composition of the sample as well as respective RI measurements. To that 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 as well as 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. Further, we employ it to estimate the mass density of trunk tissue of living zebrafish (Danio rerio) larvae. Our results enable quantifying changes of mass density estimates based on variations in the a priori assumptions. This illustrates 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.

biophysics↗

bioRxiv2022

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. We hypothesised that adipocyte shape and size changes with differentiation and lipid accumulation would be accompanied by changes in the mechanical phenotype at both the cell and tissue level. We quantified by optical diffraction tomography (ODT) 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 (MRE). 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. Since preadipocytes are mechanosensitive, tissue stiffening in diabetes might be critical to the balance between hyperplasia and hypertrophy and moreover present a potential target in the prevention of metabolic disorders.

biophysics↗

bioRxiv2022

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 {micro}m wide microfluidic channel. The fluid shear stress induces large, near 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. Roscoe1 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.

biophysics↗

bioRxiv2021

De novo identification of universal cell mechanics regulators

Cell mechanical properties determine many physiological functions, such as cell fate specification, migration, or circulation through vasculature. Identifying factors that govern the mechanical properties is therefore a subject of great interest. Here we present a mechanomics approach for establishing links between single-cell mechanical phenotype changes and the genes involved in driving them. We combine mechanical characterization of cells across a variety of mouse and human systems with machine learning-based discriminative network analysis of associated transcriptomic profiles to infer a conserved network module of five genes with putative roles in cell mechanics regulation. We validate in silico that the identified gene markers are universal, trustworthy and specific to the mechanical phenotype across the studied mouse and human systems, and demonstrate experimentally that a selected target, CAV1, changes the mechanical phenotype of cells accordingly when silenced or overexpressed. Our data-driven approach paves the way towards engineering cell mechanical properties on demand to explore their impact on physiological and pathological cell functions.

biophysics↗

bioRxiv2020

Combined fluorescence, optical diffraction tomography and Brillouin microscopy

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 epi-fluorescence imaging for explicitly measuring the Brillouin shift, RI and absolute density with specificity to fuorescently 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.

biophysics↗

bioRxiv2020

AIDeveloper: deep learning image classification in life science and beyond

Publications on artificial intelligence (AI)-based image analysis have increased drastically in recent years. However, all applications use individual solutions highly specialized for a particular task. Here, we present an easy-to-use, adaptable, open source software, called AIDeveloper (AID) to train neural nets (NN) for image classification without the need for programming. The software provides a variety of NN-architectures that can be simply selected for training. AID allows the user to apply trained models on new data, obtain metrics for classification performance, and export final models to different formats. The working principles of AID are first illustrated by training a convolutional neural net (CNN) on a large dataset consisting of images of different objects (CIFAR-10). We further explore the potential of AID by training a model to distinguish areas of differentiated and non-differentiated mesenchymal stem cells (MSCs) in culture. Additionally, we compare a conventional clinical whole blood cell count with a whole blood cell count performed by an NN-trained, using a dataset of more than 1.2 million images obtained by real-time deformability cytometry, delivering comparable results. Finally, we demonstrate how AID can be used for label-free classification of B- and T-cells derived from human blood, which currently requires costly and time-consuming sample preparation. Thus, AID can empower anyone to develop, train, and apply NNs for image classification. Moreover, models can be generated by non-programmers, exported, and used on different devices, which allows for an interdisciplinary use.

bioinformatics↗

bioRxiv2019

Using real-time fluorescence and deformability cytometry and deep learning to transfer molecular specificity to label-free sorting

The identification and separation of specific cells from heterogeneous populations is an essential prerequisite for further analysis or use. Conventional passive and active separation approaches rely on fluorescent or magnetic tags introduced to the cells of interest through molecular markers. Such labeling is time- and cost-intensive, can alter cellular properties, and might be incompatible with subsequent use, for example, in transplantation. Alternative label-free approaches utilizing morphological or mechanical features are attractive, but lack molecular specificity. Here we combine image-based real-time fluorescence and deformability cytometry (RT-FDC) with downstream cell sorting using standing surface acoustic waves (SSAW). We demonstrate basic sorting capabilities of the device by separating cell mimics and blood cell types based on fluorescence as well as deformability and other image parameters. The identification of blood sub-populations is enhanced by flow alignment and deformation of cells in the microfluidic channel constriction. In addition, the classification of blood cells using established fluorescence-based markers provides hundreds of thousands of labeled cell images used to train a deep neural network. The trained algorithm, with latency optimized to below 1 ms, is then used to identify and sort unlabeled blood cells at rates of 100 cells/sec. This approach transfers molecular specificity into label-free sorting and opens up new possibilities for basic biological research and clinical therapeutic applications.

biophysics↗

bioRxiv2019

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 neurogenesis and axon regrowth. The mechanical mechanisms contributing to successful spinal cord repair in adult zebrafish are, however, currently unknown. Here, we employ AFM-enabled nano-indentation 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 completion of repair. Tissue stiffness correlated variably with cell number density, oligodendrocyte interconnectivity, axonal orientation, and vascularization. The presented work constitutes the first quantitative mapping of the spatio-temporal 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.

biophysics↗

bioRxiv2019

Buckling of epithelium growing under spherical confinement

Many organs, such as the gut or the spine 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 to measure the stress field and the material properties of the tissue, which is 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 epithelium growth in three-dimensional confinement are sufficient to drive folding by buckling.

biophysics↗

bioRxiv2018

Intracellular mass density increase is accompanying but not sufficient for stiffening and growth arrest of yeast cells

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.

biophysics↗

bioRxiv2018

Standardized microgel beads as elastic cell mechanical probes

Cell mechanical measurements are gaining increasing interest in biological and biomedical studies. However, there are no standardized calibration particles available that permit the cross-comparison of different measurement techniques operating at different stresses and time-scales. Here we present the rational design, production, and comprehensive characterization of poly-acylamide (PAAm) microgel beads mimicking biological cells. We produced mono-disperse beads at rates of 20 - 60 kHz by means of a microfluidic droplet generator, where the pre-gel composition was adjusted to tune the beads elasticity in the range of cell and tissue relevant mechanical properties. We verified bead homogeneity by optical diffraction tomography and Brillouin microscopy. Consistent elastic behavior of microgel beads at different shear rates was confirmed by AFM-enabled nanoindentation and real-time deformability cytometry (RT-DC). The remaining inherent variability in elastic modulus was rationalized using polymer theory and effectively reduced by sorting based on forward-scattering using conventional flow cytometry. Our results show that PAAm microgel beads can be standardized as mechanical probes, to serve not only for validation and calibration of cell mechanical measurements, but also as cell-scale stress sensors.\n\nSignificance StatementOften vastly different cell mechanical properties are reported even for the same cell type when employing different measurement techniques. This discrepancy shows the urgent need for standardized calibration particles to cross-compare and validate techniques. Microgel beads can serve this purpose, but they have to fulfil specific requirements such as homogeneity, sizes and elasticities in the range of the cells, and they have to provide comparable results independent of the method applied. Here we demonstrate the standardized production of polyacrylamide microgel beads with all the features an elastic cell-mimic should have. These can not only be used as method calibration particles, but can also serve as cell-scale sensors to quantify normal and shear stresses exerted by other cells and inside tissues, enabling many new applications.

biophysics↗

bioRxiv2017

Mechanical mapping of spinal cord development and repair in living zebrafish larvae using Brillouin microscopy

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 animals 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.

biophysics↗