Characterizing Cellular Biophysical Responses to Stress by Relating Density, Deformability, and Size

Critical review of single-cell mechanotyping approaches for biomedical applications

Accurate mechanical measurements of cells has the potential to improve diagnostics, therapeutics and advance understanding of disease mechanisms, where high-resolution mechanical information can be measured by deforming individual cells. Here we evaluate recently developed techniques for measuring cell-scale stiffness properties; while many such techniques have been developed, much of the work examining single-cell stiffness is impacted by difficulties in standardization and comparability, giving rise to large variations in reported mechanical moduli. We highlight the role of underlying mechanical theories driving this variability, and note opportunities to develop novel mechanotyping devices and theoretical models that facilitate convenient and accurate mechanical characterisation. Moreover, many high-throughput approaches are confounded by factors including cell size, surface friction, natural population heterogeneity and convolution of elastic and viscous contributions to cell deformability. We nevertheless identify key approaches based on deformability cytometry as a promising direction for further development, where both high-throughput and accurate single-cell resolutions can be realized.

Measuring single-cell density with high throughput enables dynamic profiling of immune cell and drug response from patient samples

Cell density, the ratio of cell mass to volume, is an indicator of molecular crowding and therefore a fundamental determinant of cell state and function. However, existing density measurements lack the precision or throughput to quantify subtle differences in cell states, particularly in primary samples. Here we present an approach for measuring the density of 30,000 single cells per hour with a precision of 0.03% (0.0003 g/mL) by integrating fluorescence exclusion microscopy with a suspended microchannel resonator. Applying this approach to human lymphocytes, we discovered that cell density and its variation decrease as cells transition from quiescence to a proliferative state, suggesting that the level of molecular crowding decreases and becomes more regulated upon entry into the cell cycle. Using a pancreatic cancer patient-derived xenograft model, we found that the ex vivo density response of primary tumor cells to drug treatment can predict in vivo tumor growth response. Our method reveals unexpected behavior in molecular crowding during cell state transitions and suggests density as a new biomarker for functional precision medicine.

Interstitial-fluid shear stresses induced by vertically oscillating head motion lower blood pressure in hypertensive rats and humans

The mechanisms by which physical exercise benefits brain functions are not fully understood. Here, we show that vertically oscillating head motions mimicking mechanical accelerations experienced during fast walking, light jogging or treadmill running at a moderate velocity reduce the blood pressure of rats and human adults with hypertension. In hypertensive rats, shear stresses of less than 1 Pa resulting from interstitial-fluid flow induced by such passive head motions reduced the expression of the angiotensin II type-1 receptor in astrocytes in the rostral ventrolateral medulla, and the resulting antihypertensive effects were abrogated by hydrogel introduction that inhibited interstitial-fluid movement in the medulla. Our findings suggest that oscillatory mechanical interventions could be used to elicit antihypertensive effects.

Real-time online monitoring of insect cell proliferation and baculovirus infection using digital differential holographic microscopy and machine learning

Real-time, detailed online information on cell cultures is essential for understanding modern biopharmaceutical production processes. The determination of key parameters, such as cell density and viability, is usually based on the offline sampling of bioreactors. Gathering offline samples is invasive, has a low time resolution, and risks altering or contaminating the production process. In contrast, measuring process parameters online provides more safety for the process, has a high time resolution, and thus can aid in timely process control actions. We used online double differential digital holographic microscopy (D3HM) and machine learning to perform non-invasive online cell concentration and viability monitoring of insect cell cultures in bioreactors. The performance of D3HM and the machine learning model was tested for a selected variety of baculovirus constructs, products, and multiplicities of infection (MOI). The results show that with online holographic microscopy insect cell proliferation and baculovirus infection can be monitored effectively in real time with high resolution for a broad range of process parameters and baculovirus constructs. The high-resolution data generated by D3HM showed the exact moment of peak cell densities and temporary events caused by feeding. Furthermore, D3HM allowed us to obtain information on the state of the cell culture at the individual cell level. Combining this detailed, real-time information about cell cultures with methodical machine learning models can increase process understanding, aid in decision-making, and allow for timely process control actions during bioreactor production of recombinant proteins.

Volumetric mass density measurements of mesenchymal stem cells in suspension using a density meter

To use regeneratively active cells for cell therapeutic applications, the cells must be isolated from their resident tissues. Different isolation procedures subject these cells to varying degrees of mechanical strain, which can affect the yield of cell number and viability. Knowledge of cell volumetric mass density is important for experimental and numerical optimization of these procedures. Although methods for measuring cell volumetric mass density already exist, they either consume much time and cell material or require a special setup. Therefore, we developed a user-friendly method that is based on the use of readily available instrumentation. The newly developed method is predicated on the linear relationship between the volumetric mass density of the cell suspension and the volumetric mass density, number, and diameter of the cells in the suspension. We used this method to determine the volumetric mass density of mesenchymal stem cells (MSCs) and compared it to results from the established density centrifugation.

Advanced density-based methods for the characterization of materials, binding events, and kinetics

Investigations of the densities of chemicals and materials bring valuable insights into the fundamental understanding of matter and processes. Recently, advanced density-based methods have been developed with wide measurement ranges (i.e. 0-23 g cm^-3), high resolutions (i.e. 10^-6 g cm^-3), compatibility with different types of samples and the requirement of extremely low volumes of sample (as low as a single cell). Certain methods, such as magnetic levitation, are inexpensive, portable and user-friendly. Advanced density-based methods are, therefore, beneficially used to obtain absolute density values, composition of mixtures, characteristics of binding events, and kinetics of chemical and biological processes. Herein, the principles and applications of magnetic levitation, acoustic levitation, electrodynamic balance, aqueous multiphase systems, and suspended microchannel resonators for materials science are discussed.

Quantitative Imaging of Intracellular Density with Ratiometric Stimulated Raman Scattering Microscopy

Cell size and density are tightly controlled in mammalian cells. They impact a wide range of physiological functions, including osmoregulation, tissue homeostasis, and growth regulation. Compared to size, density variation for a given cell type is typically much smaller, implying that cell-type-specific density plays an important role in cell function. However, little is known about how cell density affects cell function or how it is regulated. Current tools for intracellular cell density measurements are limited to either suspended cells or cells grown on 2D substrates, neither of which recapitulate the physiology of single cells in intact tissue. While optical measurements have the potential to noninvasively measure cell density in situ, light scattering in multicellular systems prevents direct quantification. Here, we introduce an intracellular density imaging technique based on ratiometric stimulated Raman scattering microscopy (rSRS). It uses intrinsic vibrational information from intracellular macromolecules to quantify dry mass density. Moreover, water is used as an internal standard to correct for aberration and light scattering effects. We demonstrate real-time measurement of intracellular density and show that density is tightly regulated across different cell types and can be used to differentiate cell types as well as cell states. We further demonstrate dynamic imaging of density change in response to osmotic challenge as well as intracellular density imaging of a 3D tumor spheroid. Our technique has the potential for imaging intracellular density in intact tissue and understanding density regulation and its role in tissue homeostasis.

A mechano-osmotic feedback couples cell volume to the rate of cell deformation

Mechanics has been a central focus of physical biology in the past decade. In comparison, how cells manage their size is less understood. Here we show that a parameter central to both the physics and the physiology of the cell, its volume, depends on a mechano-osmotic coupling. We found that cells change their volume depending on the rate at which they change shape, when they spontaneously spread are externally deformed. Cells undergo slow deformation at constant volume, while fast deformation leads to volume loss. We propose a mechano-sensitive pump and leak model to explain this phenomenon. Our model and experiments suggest that volume modulation depends on the state of the actin cortex and the coupling of ion fluxes to membrane tension. This mechano-osmotic coupling defines a membrane tension homeostasis module constantly at work in cells, causing volume fluctuations associated with fast cell shape changes, with potential consequences on cellular physiology.

Physical Cytometry: Detecting Mass-Related Properties of Single Cells

The physical properties of a single cell, such as mass, volume, and density, are important indications of the cell's metabolic characteristics and homeostasis. Precise measurement of a single cell's mass has long been a challenge due to its minute size. It is only in the past 10 years that a variety of instruments for measuring living cellular mass have emerged with the development of MEMS, microfluidics, and optics technologies. In this review, we discuss the current developments of physical cytometry for quantifying mass-related physical properties of single cells, highlighting the working principle, applications, and unique merits. The review mainly covers these measurement methods: single-cell mass cytometry, levitation image cytometry, suspended microchannel resonator, phase-shifting interferometry, and opto-electrokinetics cell manipulation. Comparisons are made between these methods in terms of throughput, content, invasiveness, compatibility, and precision. Some typical applications of these methods in pathological diagnosis, drug efficacy evaluation, disease treatment, and other related fields are also discussed in this work.

Cellular and biomolecular detection based on suspended microchannel resonators

Suspended microchannel resonators (SMRs) have been developed to measure the buoyant mass of single micro-/nanoparticles and cells suspended in a liquid. They have significantly improved the mass resolution with the aid of vacuum packaging and also increased measurement throughput by fast resonance frequency tracking while target objects travel through the microchannel without stopping or even slowing down. Since their invention, various biological applications have been enabled, including simultaneous measurements of cell growth and cell cycle progression, and measurements of disease associated physicochemical change, to name a few. Extension and advancement towards other promising applications with SMRs are continuously ongoing by adding multiple functionalities or incorporating other complementary analytical metrologies. In this paper, we will thoroughly review the development history, basic and advanced operations, and key applications of SMRs to introduce them to researchers working in biological and biomedical sciences who mostly rely on classical and conventional methodologies. We will also provide future perspectives and projections for SMR technologies.

Computational models of cancer cell transport through the microcirculation

The transport of cancerous cells through the microcirculation during metastatic spread encompasses several interdependent steps that are not fully understood. Computational models which resolve the cellular-scale dynamics of complex microcirculatory flows offer considerable potential to yield needed insights into the spread of cancer as a result of the level of detail that can be captured. In recent years, in silico methods have been developed that can accurately and efficiently model the circulatory flows of cancer and other biological cells. These computational methods are capable of resolving detailed fluid flow fields which transport cells through tortuous physiological geometries, as well as the deformation and interactions between cells, cell-to-endothelium interactions, and tumor cell aggregates, all of which play important roles in metastatic spread. Such models can provide a powerful complement to experimental works, and a promising approach to recapitulating the endogenous setting while maintaining control over parameters such as shear rate, cell deformability, and the strength of adhesive binding to better understand tumor cell transport. In this review, we present an overview of computational models that have been developed for modeling cancer cells in the microcirculation, including insights they have provided into cell transport phenomena.

Hydrodynamic assisted multiparametric particle spectrometry

The real-time analysis of single analytes in flow is becoming increasingly relevant in cell biology. In this work, we theoretically predict and experimentally demonstrate hydrodynamic focusing with hollow nanomechanical resonators by using an interferometric system which allows the optical probing of flowing particles and tracking of the fundamental mechanical mode of the resonator. We have characterized the hydrodynamic forces acting on the particles, which will determine their velocity depending on their diameter. By using the parameters simultaneously acquired: frequency shift, velocity and reflectivity, we can unambiguously classify flowing particles in real-time, allowing the measurement of the mass density: 1.35 ± 0.07 g·mL^-1 for PMMA and 1.7 ± 0.2 g·mL^-1 for silica particles, which perfectly agrees with the nominal values. Once we have tested our technique, MCF-7 human breast adenocarcinoma cells are characterized (1.11 ± 0.08 g·mL^-1) with high throughput (300 cells/minute) observing a dependency with their size, opening the door for individual cell cycle studies.

Particle Detection and Characterization for Biopharmaceutical Applications: Current Principles of Established and Alternative Techniques

Detection and characterization of particles in the visible and subvisible size range is critical in many fields of industrial research. Commercial particle analysis systems have proliferated over the last decade. Despite that growth, most systems continue to be based on well-established principles, and only a handful of new approaches have emerged. Identifying the right particle-analysis approach remains a challenge in research and development. The choice depends on each individual application, the sample, and the information the operator needs to obtain. In biopharmaceutical applications, particle analysis decisions must take product safety, product quality, and regulatory requirements into account. Biopharmaceutical process samples and formulations are dynamic, polydisperse, and very susceptible to chemical and physical degradation: improperly handled product can degrade, becoming inactive or in specific cases immunogenic. This article reviews current methods for detecting, analyzing, and characterizing particles in the biopharmaceutical context. The first part of our article represents an overview about current particle detection and characterization principles, which are in part the base of the emerging techniques. It is very important to understand the measuring principle, in order to be adequately able to judge the outcome of the used assay. Typical principles used in all application fields, including particle–light interactions, the Coulter principle, suspended microchannel resonators, sedimentation processes, and further separation principles, are summarized to illustrate their potentials and limitations considering the investigated samples. In the second part, we describe potential technical approaches for biopharmaceutical particle analysis as some promising techniques, such as nanoparticle tracking analysis (NTA), micro flow imaging (MFI), tunable resistive pulse sensing (TRPS), flow cytometry, and the space- and time-resolved extinction profile (STEP^®) technology.

Deep-learning-assisted biophysical imaging cytometry at massive throughput delineates cell population heterogeneity

The association of the intrinsic optical and biophysical properties of cells to homeostasis and pathogenesis has long been acknowledged. Defining these label-free cellular features obviates the need for costly and time-consuming labelling protocols that perturb the living cells. However, wide-ranging applicability of such label-free cell-based assays requires sufficient throughput, statistical power and sensitivity that are unattainable with current technologies. To close this gap, we present a large-scale, integrative imaging flow cytometry platform and strategy that allows hierarchical analysis of intrinsic morphological descriptors of single-cell optical and mass density within a population of millions of cells. The optofluidic cytometry system also enables the synchronous single-cell acquisition of and correlation with fluorescently labeled biochemical markers. Combined with deep neural network and transfer learning, this massive single-cell profiling strategy demonstrates the label-free power to delineate the biophysical signatures of the cancer subtypes, to detect rare populations of cells in the heterogeneous samples (10-5), and to assess the efficacy of targeted therapeutics. This technique could spearhead the development of optofluidic imaging cell-based assays that stratify the underlying physiological and pathological processes based on the information-rich biophysical cellular phenotypes.

Magnetic Levitation in Chemistry, Materials Science, and Biochemistry

All matter has density. The recorded uses of density to characterize matter date back to as early as ca. 250 BC, when Archimedes was believed to have solved "The Puzzle of The King's Crown" using density.^[1] Today, measurements of density are used to separate and characterize a range of materials (including cells and organisms), and their chemical and/or physical changes in time and space. This Review describes a density-based technique-magnetic levitation (which we call "MagLev" for simplicity)-developed and used to solve problems in the fields of chemistry, materials science, and biochemistry. MagLev has two principal characteristics-simplicity, and applicability to a wide range of materials-that make it useful for a number of applications (for example, characterization of materials, quality control of manufactured plastic parts, self-assembly of objects in 3D, separation of different types of biological cells, and bioanalyses). Its simplicity and breadth of applications also enable its use in low-resource settings (for example-in economically developing regions-in evaluating water/food quality, and in diagnosing disease).

The promise of single-cell mechanophenotyping for clinical applications

Cancer is the second leading cause of death worldwide. Despite the immense research focused in this area, one is still not able to predict disease trajectory. To overcome shortcomings in cancer disease study and monitoring, we describe an exciting research direction: cellular mechanophenotyping. Cancer cells must overcome many challenges involving external forces from neighboring cells, the extracellular matrix, and the vasculature to survive and thrive. Identifying and understanding their mechanical behavior in response to these forces would advance our understanding of cancer. Moreover, used alongside traditional methods of immunostaining and genetic analysis, mechanophenotyping could provide a comprehensive view of a heterogeneous tumor. In this perspective, we focus on new technologies that enable single-cell mechanophenotyping. Single-cell analysis is vitally important, as mechanical stimuli from the environment may obscure the inherent mechanical properties of a cell that can change over time. Moreover, bulk studies mask the heterogeneity in mechanical properties of single cells, especially those rare subpopulations that aggressively lead to cancer progression or therapeutic resistance. The technologies on which we focus include atomic force microscopy, suspended microchannel resonators, hydrodynamic and optical stretching, and mechano-node pore sensing. These technologies are poised to contribute to our understanding of disease progression as well as present clinical opportunities.

Various Nucleolar Stress Inducers Result in Highly Distinct Changes in Water, Dry Mass and Elemental Content in Cancerous Cell Compartments: Investigation Using a Nano-Analytical Approach

Rationale: Numerous chemotherapeutic drugs that affect ribosome biogenesis in the nucleolus induce nucleolar stress. Improving our understanding of the effects of these drugs will require uncovering and comparing their impact on several biophysical parameters of the major cell compartments. Here, we quantified the water content and dry mass of cancerous cells treated with CX-5461, DRB or DAM to calculate macromolecular crowding and the volume occupied by free water, as well as elemental content. Methods: HeLa-H2B-GFP cells were treated with CX-5461, DRB or DAM. Water content and dry mass were measured in numerous regions of interest of ultrathin cryo-sections by quantitative scanning transmission electron microscope dark-field imaging and the elements quantified by energy dispersive X-ray spectrometry. The data were used to calculate macromolecular crowding and the volume occupied by free water in all cell compartments of control and treated cells. Hydrophobic and unfolded proteins were revealed by 8-Anilinonaphtalene-1-sulfonic acid (ANS) staining and imaging by two-photon microscopy. Immunolabeling of UBF, pNBS1 and pNF-κB was carried out and the images acquired with a confocal microscope for 3D imaging to address whether the localization of these proteins changes in treated cells. Results: Treatment with CX-5461, DRB or DAM induced completely different changes in macromolecular crowding and elemental content. Macromolecular crowding and elemental content were much higher in CX-5461-treated, moderately higher in DRB-treated, and much lower in DAM-treated cells than control cells. None of the drugs alone induced nucleolar ANS staining but it was induced by heat-shock of control cells and cells previously treated with DAM. UBF and pNBS1 were systematically co-localized in the nucleolus of CX-5461- and DAM-treated cells. pNF-κB only localized to the nucleolar caps of pre-apoptotic DAM-treated cells. Conclusion: We directly quantified water and ion content in cell compartments using cryo-correlative electron microscopy. We show that different chemotherapeutic nucleolar stress inducers result in distinctive, thus far-unrecognized changes in macromolecular crowding and elemental content which are known to modify cell metabolism. Moreover we were able to correlate these changes to the sensitivity of treated cells to heat-shock and the behavior of nucleolar pNBS1 and pNF-κB.

Determining therapeutic susceptibility in multiple myeloma by single-cell mass accumulation

Multiple myeloma (MM) has benefited from significant advancements in treatment that have improved outcomes and reduced morbidity. However, the disease remains incurable and is characterized by high rates of drug resistance and relapse. Consequently, methods to select the most efficacious therapy are of great interest. Here we utilize a functional assay to assess the ex vivo drug sensitivity of single multiple myeloma cells based on measuring their mass accumulation rate (MAR). We show that MAR accurately and rapidly defines therapeutic susceptibility across human multiple myeloma cell lines to a gamut of standard-of-care therapies. Finally, we demonstrate that our MAR assay, without the need for extended culture ex vivo, correctly defines the response of nine patients to standard-of-care drugs according to their clinical diagnoses. This data highlights the MAR assay in both research and clinical applications as a promising tool for predicting therapeutic response using clinical samples.

Multiple myeloma is characterized by high rates of drug resistance and relapse. Here the authors utilize a functional assay to assess the ex vivo drug sensitivity of single multiple myeloma cells based on measuring the mass accumulation rate of individual cells.

Drug sensitivity of single cancer cells is predicted by changes in mass accumulation rate

Assays that can determine the response of tumor cells to cancer therapeutics could greatly aid the selection of drug regimens for individual patients. However, the utility of current functional assays is limited, and predictive genetic biomarkers are available for only a small fraction of cancer therapies. We found that the single-cell mass accumulation rate (MAR), profiled over many hours with a suspended microchannel resonator, accurately defined the drug sensitivity or resistance of glioblastoma and B-cell acute lymphocytic leukemia cells. MAR revealed heterogeneity in drug sensitivity not only between different tumors, but also within individual tumors and tumor-derived cell lines. MAR measurement predicted drug response using samples as small as 25 μl of peripheral blood while maintaining cell viability and compatibility with downstream characterization. MAR measurement is a promising approach for directly assaying single-cell therapeutic responses and for identifying cellular subpopulations with phenotypic resistance in heterogeneous tumors.

Biophysical changes reduce energetic demand in growth factor-deprived lymphocytes

Changes to the biophysical properties of lymphocytes are identified as an adaptive response to acute nutrient stress that occurs before the induction of autophagy.

Cytokine regulation of lymphocyte growth and proliferation is essential for matching nutrient consumption with cell state. Here, we examine how cellular biophysical changes that occur immediately after growth factor depletion promote adaptation to reduced nutrient uptake. After growth factor withdrawal, nutrient uptake decreases, leading to apoptosis. Bcl-x_L expression prevents cell death, with autophagy facilitating long-term cell survival. However, autophagy induction is slow relative to the reduction of nutrient uptake, suggesting that cells must engage additional adaptive mechanisms to respond initially to growth factor depletion. We describe an acute biophysical response to growth factor withdrawal, characterized by a simultaneous decrease in cell volume and increase in cell density, which occurs before autophagy initiation and is observed in both FL5.12 Bcl-x_L cells depleted of IL-3 and primary CD8⁺ T cells depleted of IL-2 that are differentiating toward memory cells. The response reduces cell surface area to minimize energy expenditure while conserving biomass, suggesting that the biophysical properties of cells can be regulated to promote survival under conditions of nutrient stress.