Direct observation of mammalian cell growth and size regulation

Rapid mechanical phenotyping of breast cancer cells based on stochastic intracellular fluctuations

Predicting the phenotypic impact of genetic variants and treatments is crucial in cancer genetics and precision oncology. Here, we have developed a noise decorrelation method that enables quantitative phase imaging (QPI) with the capability for label-free noninvasive mapping of intracellular dry mass fluctuations within the millisecond-to-second timescale regime, previously inaccessible due to temporal phase noise. Applied to breast cancer cells, this method revealed regions driven by thermal forces and regions of intense activity fueled by ATP hydrolysis. Intriguingly, as malignancy increases, the cells strategically expand these active regions to satisfy increasing energy demands. We propose parameters encapsulating key information about the spatiotemporal distribution of intracellular fluctuations, enabling precise phenotyping. This technique addresses the need for accurate, rapid functional screening methods in cancer medicine.

A bi-component model to assess the rheology of soft cellular aggregates probed using the micropipette aspiration technique

The micro-pipette aspiration technique is a classical experiment used to characterize the physical properties of inert fluids and biological soft materials such as cellular aggregates. The physical parameters of the fluid, as viscosity and interfacial tension, are obtained by studying how the fluid enters the pipette when the suction pressure is increased and how it relaxes when the suction pressure is put to zero. A mathematical model representative of the experiment is needed to extrapolate the physical parameters of the fluid-like matter; however, for biological materials as cells or cell aggregates mathematical models are always based on strong starting hypotheses that impact the significance of the identified parameters. In this article, starting from the bi-constituent nature of the cell aggregate, we derive a general mathematical model based of a Cahn-Hilliard-Navier-Stokes set of equations. The model is applied to describe quantitatively the aspiration-retraction dynamics of a cell-aggregate into and out of a pipette. We demonstrate the predictive capability of the model and highlight the impact of the assumptions made on the identified parameters by studying two cases: one with a non-wetting condition between the cells and the wall of the pipette (classical assumption in the literature) and the second one, which is more realistic, with a partial wetting condition (contact angle θs = 150°). Furthermore, our results provide a purely physical explanation to the asymmetry between the aspiration and retraction responses which is alternative to the proposed hypothesis of an mechano-responsive alteration of the surface tension of the cell aggregate. STATEMENT OF SIGNIFICANCE: Our study introduces a general mathematical model, based on the Cahn-Hilliard-Navier-Stokes equations, tailored to model micro-pipette aspiration of cell aggregates. The model accounts for the multi-component structure of the cell aggregate and its intrinsic viscoelastic rheology. By challenging prevailing assumptions, particularly regarding perfect non-wetting conditions and the mechano-responsive alteration of cell surface tension, we demonstrate the reliability of the mathematical model and elucidate the mechanisms at play, offering a purely physical explanation for observed asymmetries between the aspiration and retraction stages of the experiment.

Eukaryotic cell size regulation and its implications for cellular function and dysfunction

Depending on cell type, environmental inputs, and disease, the cells in the human body can have widely different sizes. In recent years, it has become clear that cell size is a major regulator of cell function. However, we are only beginning to understand how the optimization of cell function determines a given cell's optimal size. Here, we review currently known size control strategies of eukaryotic cells and the intricate link of cell size to intracellular biomolecular scaling, organelle homeostasis, and cell cycle progression. We detail the cell size-dependent regulation of early development and the impact of cell size on cell differentiation. Given the importance of cell size for normal cellular physiology, cell size control must account for changing environmental conditions. We describe how cells sense environmental stimuli, such as nutrient availability, and accordingly adapt their size by regulating cell growth and cell cycle progression. Moreover, we discuss the correlation of pathological states with misregulation of cell size and how for a long time this was considered a downstream consequence of cellular dysfunction. We review newer studies that reveal a reversed causality, with misregulated cell size leading to pathophysiological phenotypes such as senescence and aging. In summary, we highlight the important roles of cell size in cellular function and dysfunction, which could have major implications for both diagnostics and treatment in the clinic.

Size-related variability of oxygen consumption rates in individual human hepatic cells

Accurate descriptions of the variability in single-cell oxygen consumption and its size-dependency are key to establishing more robust tissue models. By combining microfabricated devices with multiparameter identification algorithms, we demonstrate that single human hepatocytes exhibit an oxygen level-dependent consumption rate and that their maximal oxygen consumption rate is significantly lower than that of typical hepatic cell cultures. Moreover, we found that clusters of two or more cells competing for a limited oxygen supply reduced their maximal consumption rate, highlighting their ability to adapt to local resource availability and the presence of nearby cells. We used our approach to characterize the covariance of size and oxygen consumption rate within a cell population, showing that size matters, since oxygen metabolism covaries lognormally with cell size. Our study paves the way for linking the metabolic activity of single human hepatocytes to their tissue- or organ-level metabolism and describing its size-related variability through scaling laws.

Constant surface area-to-volume ratio during cell growth as a design principle in mammalian cells

All cells are subject to geometric constraints, such as surface area-to-volume (SA/V) ratio, that impact cell functions and force biological adaptations. Like the SA/V ratio of a sphere, it is generally assumed that the SA/V ratio of cells decreases as cell size increases. Here, we investigate this in near-spherical mammalian cells using single-cell measurements of cell mass and surface proteins, as well as imaging of plasma membrane morphology. We find that the SA/V ratio remains surprisingly constant as cells grow larger. This observation is largely independent of the cell cycle and the amount of cell growth. Consequently, cell growth results in increased plasma membrane folding, which simplifies cellular design by ensuring sufficient membrane area for cell division, nutrient uptake and deformation at all cell sizes.

Microfluidic characterization of single-cell biophysical properties and the applications in cancer diagnosis

Single-cell biophysical properties play a crucial role in regulating cellular physiological states and functions, demonstrating significant potential in the fields of life sciences and clinical diagnostics. Therefore, over the last few decades, researchers have developed various detection tools to explore the relationship between the biophysical changes of biological cells and human diseases. With the rapid advancement of modern microfabrication technology, microfluidic devices have quickly emerged as a promising platform for single-cell analysis offering advantages including high-throughput, exceptional precision, and ease of manipulation. Consequently, this paper provides an overview of the recent advances in microfluidic analysis and detection systems for single-cell biophysical properties and their applications in the field of cancer. The working principles and latest research progress of single-cell biophysical property detection are first analyzed, highlighting the significance of electrical and mechanical properties. The development of data acquisition and processing methods for real-time, high-throughput, and practical applications are then discussed. Furthermore, the differences in biophysical properties between tumor and normal cells are outlined, illustrating the potential for utilizing single-cell biophysical properties for tumor cell identification, classification, and drug response assessment. Lastly, we summarize the limitations of existing microfluidic analysis and detection systems in single-cell biophysical properties, while also pointing out the prospects and future directions of their applications in cancer diagnosis and treatment.

Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease

Efforts to cure BCR::ABL1 B cell acute lymphoblastic leukemia (Ph+ ALL) solely through inhibition of ABL1 kinase activity have thus far been insufficient despite the availability of tyrosine kinase inhibitors (TKIs) with broad activity against resistance mutants. The mechanisms that drive persistence within minimal residual disease (MRD) remain poorly understood and therefore untargeted. Utilizing 13 patient-derived xenograft (PDX) models and clinical trial specimens of Ph+ ALL, we examined how genetic and transcriptional features co-evolve to drive progression during prolonged TKI response. Our work reveals a landscape of cooperative mutational and transcriptional escape mechanisms that differ from those causing resistance to first generation TKIs. By analyzing MRD during remission, we show that the same resistance mutation can either increase or decrease cellular fitness depending on transcriptional state. We further demonstrate that directly targeting transcriptional state-associated vulnerabilities at MRD can overcome BCR::ABL1 independence, suggesting a new paradigm for rationally eradicating MRD prior to relapse. Finally, we illustrate how cell mass measurements of leukemia cells can be used to rapidly monitor dominant transcriptional features of Ph+ ALL to help rationally guide therapeutic selection from low-input samples.

A novel cell biological tool to explain mechanics and dynamics in fission yeast

The Rho guanosine triphosphatase hydrolase enzyme (GTPase) is required for the control of the actin cytoskeleton, but its activation in vivo condition is unknown. The study's goal was to find a new synthetic nanobody VHH (P-36 tagged with mNeonGreen) that interacts strongly with the Rho GTPase. We present the first novel synthetic nanobody, VHH (P-36 tagged with mNeonGreen), tested in fission yeast cells and found to have a particular interaction with Rho1GTPase. Plasmids were constructed by using of certain enzymes to digest the pDUAL-pef1a vector plasmid to produce a protein that was encoded by cloned genes. A varied VHH library was created synthetically, then transformed into yeast cells, and positive clones were chosen using chemical agents. To investigate protein interactions and cellular reactions, several studies were carried out, such as live cell imaging, growth curve analysis, coimmunoprecipitation, structural analysis, and cell therapies. Prism and RStudio were used for the statistical analysis. The presence of VHH (P-36) has no effect on the growth pattern making it an appropriate model for studying cytokinesis in vivo. According to a computational biological study, its affinity to interact with Rho1GTPase with all the complementarity-determining region (CDR) regions found on VHH (P-36) is extremely strong. We were able to track its subcellular target by localization using a fluorescent confocal microscope, ensuring the maintenance of cell polarity and morphology. Spheroplast analysis revealed a circular-shaped cell with an even distribution of Rho1 tagged VHH (P-36), indicating that the interaction occurs near the plasma membrane. The introduction of latrunculin-A (Lat-A) disrupted Rho GTPase localization, demonstrating the control over actin production, and the cell did not show evidence of mitotic phase commencement while Lat-A was present. Finally, this important biological tool can aid in our understanding of the mechanics and dynamics of cytokinesis in relation to Rho1GTPase.

Monitoring the mass, eigenfrequency, and quality factor of mammalian cells

The regulation of mass is essential for the development and homeostasis of cells and multicellular organisms. However, cell mass is also tightly linked to cell mechanical properties, which depend on the time scales at which they are measured and change drastically at the cellular eigenfrequency. So far, it has not been possible to determine cell mass and eigenfrequency together. Here, we introduce microcantilevers oscillating in the Ångström range to monitor both fundamental physical properties of the cell. If the oscillation frequency is far below the cellular eigenfrequency, all cell compartments follow the cantilever motion, and the cell mass measurements are accurate. Yet, if the oscillating frequency approaches or lies above the cellular eigenfrequency, the mechanical response of the cell changes, and not all cellular components can follow the cantilever motions in phase. This energy loss caused by mechanical damping within the cell is described by the quality factor. We use these observations to examine living cells across externally applied mechanical frequency ranges and to measure their total mass, eigenfrequency, and quality factor. The three parameters open the door to better understand the mechanobiology of the cell and stimulate biotechnological and medical innovations.

Structural biases in disordered proteins are prevalent in the cell

Intrinsically disordered proteins and protein regions (IDPs) are prevalent in all proteomes and are essential to cellular function. Unlike folded proteins, IDPs exist in an ensemble of dissimilar conformations. Despite this structural plasticity, intramolecular interactions create sequence-specific structural biases that determine an IDP ensemble's three-dimensional shape. Such structural biases can be key to IDP function and are often measured in vitro, but whether those biases are preserved inside the cell is unclear. Here we show that structural biases in IDP ensembles found in vitro are recapitulated inside human-derived cells. We further reveal that structural biases can change in a sequence-dependent manner due to changes in the intracellular milieu, subcellular localization, and intramolecular interactions with tethered well-folded domains. We propose that the structural sensitivity of IDP ensembles can be leveraged for biological function, can be the underlying cause of IDP-driven pathology or can be used to design disorder-based biosensors and actuators.

Simultaneous Optical and Mechanical Sensing Based on Optomechanical Resonators

Optical and mechanical resonators have each been abundantly employed in sensing applications, albeit following separate development. Here we show that bringing together optical and mechanical resonances in a unique sensing device significantly improves the sensor performance. To that purpose, we employ nanoscale optomechanical disk resonators that simultaneously support high quality optical and mechanical modes localized in tiny volumes, which provide extraordinary sensitivities. We perform environmental sensing, but the conclusions of our work extend to other sensing applications. First, we determine optical and mechanical responsivities to temperature and relative humidity changes. Second, by characterizing mechanical and optical frequency stabilities, we determine the corresponding limits of detection. Mechanical modes appear more sensitive to relative humidity changes, while optical modes appear more sensitive to temperature ones, reaching, respectively, 0.05% and 0.6 mK of independent resolution. We then prove that simultaneous optical and mechanical monitoring enables disentangling both effects and demonstrates 0.1% and 1 mK resolution, even considering that both parameters may change at the same time. Finally, we highlight the importance of actively tracking the optical mode when optomechanical sensor devices. Not doing so enforces tedious independent calibration, influences the device sensitivity during the experiment, and shortens the sensing range. The present work hence clarifies the requirements for the optimal operation of optomechanical sensors, which will be of importance for chemical and biological sensing.

Cell size homeostasis is tightly controlled throughout the cell cycle

To achieve a stable size distribution over multiple generations, proliferating cells require a means of counteracting stochastic noise in the rate of growth, the time spent in various phases of the cell cycle, and the imprecision in the placement of the plane of cell division. In the most widely accepted model, cell size is thought to be regulated at the G1/S transition, such that cells smaller than a critical size pause at the end of G1 phase until they have accumulated mass to a predetermined size threshold, at which point the cells proceed through the rest of the cell cycle. However, a model, based solely on a specific size checkpoint at G1/S, cannot readily explain why cells with deficient G1/S control mechanisms are still able to maintain a very stable cell size distribution. Furthermore, such a model would not easily account for stochastic variation in cell size during the subsequent phases of the cell cycle, which cannot be anticipated at G1/S. To address such questions, we applied computationally enhanced quantitative phase microscopy (ceQPM) to populations of cultured human cell lines, which enables highly accurate measurement of cell dry mass of individual cells throughout the cell cycle. From these measurements, we have evaluated the factors that contribute to maintaining cell mass homeostasis at any point in the cell cycle. Our findings reveal that cell mass homeostasis is accurately maintained, despite disruptions to the normal G1/S machinery or perturbations in the rate of cell growth. Control of cell mass is generally not confined to regulation of the G1 length. Instead mass homeostasis is imposed throughout the cell cycle. In the cell lines examined, we find that the coefficient of variation (CV) in dry mass of cells in the population begins to decline well before the G1/S transition and continues to decline throughout S and G2 phases. Among the different cell types tested, the detailed response of cell growth rate to cell mass differs. However, in general, when it falls below that for exponential growth, the natural increase in the CV of cell mass is effectively constrained. We find that both mass-dependent cell cycle regulation and mass-dependent growth rate modulation contribute to reducing cell mass variation within the population. Through the interplay and coordination of these 2 processes, accurate cell mass homeostasis emerges. Such findings reveal previously unappreciated and very general principles of cell size control in proliferating cells. These same regulatory processes might also be operative in terminally differentiated cells. Further quantitative dynamical studies should lead to a better understanding of the underlying molecular mechanisms of cell size control.

Directed evolution of biomass intensive CHO cells by adaptation to sub-physiological temperature

We report a simple and effective means to increase the biosynthetic capacity of host CHO cells. Lonza proprietary CHOK1SV® cells were evolved by serial sub-culture for over 150 generations at 32 °C. During this period the specific proliferation rate of hypothermic cells gradually recovered to become comparable to that of cells routinely maintained at 37 °C. Cold-adapted cell populations exhibited (1) a significantly increased volume and biomass content (exemplified by total RNA and protein), (2) increased mitochondrial function, (3) an increased antioxidant capacity, (4) altered central metabolism, (5) increased transient and stable productivity of a model IgG4 monoclonal antibody and Fc-fusion protein, and (6) unaffected recombinant protein N-glycan processing. This phenotypic transformation was associated with significant genome-scale changes in both karyotype and the relative abundance of thousands of cellular mRNAs across numerous functional groups. Taken together, these observations provide evidence of coordinated cellular adaptations to sub-physiological temperature. These data reveal the extreme genomic/functional plasticity of CHO cells, and that directed evolution is a viable genome-scale cell engineering strategy that can be exploited to create host cells with an increased cellular capacity for recombinant protein production.

The Plateau in Muscle Growth with Resistance Training: An Exploration of Possible Mechanisms

It is hypothesized that there is likely a finite ability for muscular adaptation. While it is difficult to distinguish between a true plateau following a long-term training period and short-term stalling in muscle growth, a plateau in muscle growth has been attributed to reaching a genetic potential, with limited discussion on what might physiologically contribute to this muscle growth plateau. The present paper explores potential physiological factors that may drive the decline in muscle growth after prolonged resistance training. Overall, with chronic training, the anabolic signaling pathways may become more refractory to loading. While measures of anabolic markers may have some predictive capabilities regarding muscle growth adaptation, they do not always demonstrate a clear connection. Catabolic processes may also constrain the ability to achieve further muscle growth, which is influenced by energy balance. Although speculative, muscle cells may also possess cell scaling mechanisms that sense and regulate their own size, along with molecular brakes that hinder growth rate over time. When considering muscle growth over the lifespan, there comes a point when the anabolic response is attenuated by aging, regardless of whether or not individuals approach their muscle growth potential. Our goal is that the current review opens avenues for future experimental studies to further elucidate potential mechanisms to explain why muscle growth may plateau.

Plasmonic Functional Assay Platform Determines the Therapeutic Profile of Cancer Cells

Functional assay platforms could identify the biophysical properties of cells and their therapeutic response to drug treatments. Despite their strong ability to assess cellular pathways, functional assays require large tissue samples, long-term cell culture, and bulk measurements. Even though such a drawback is still valid, these limitations did not hinder the interest in these platforms for their capacity to reveal drug susceptibility. Some of the limitations could be overcome with single-cell functional assays by identifying subpopulations using small sample volumes. Along this direction, in this article, we developed a high-throughput plasmonic functional assay platform to identify the growth profile of cells and their therapeutic profile under therapies using mass and growth rate statistics of individual cells. Our technology could determine populations' growth profiles using the growth rate data of multiple single cells of the same population. Evaluating spectral variations based on the plasmonic diffraction field intensity images in real time, we could simultaneously monitor the mass change for the cells within the field of view of a camera with the capacity of > ∼500 cells/h scanning rate. Our technology could determine the therapeutic profile of cells under cancer drugs within few hours, while the classical techniques require days to show reduction in viability due to antitumor effects. The platform could reveal the heterogeneity within the therapeutic profile of populations and determine subpopulations showing resistance to drug therapies. As a proof-of-principle demonstration, we studied the growth profile of MCF-7 cells and their therapeutic behavior to standard-of-care drugs that have antitumor effects as shown in the literature, including difluoromethylornithine (DFMO), 5-fluorouracil (5-FU), paclitaxel (PTX), and doxorubicin (Dox). We successfully demonstrated the resistant behavior of an MCF-7 variant that could survive in the presence of DFMO. More importantly, we could precisely identify synergic and antagonistic effects of drug combinations based on the order of use in cancer therapy. Rapidly assessing the therapeutic profile of cancer cells, our plasmonic functional assay platform could be used to reveal personalized drug therapies for cancer patients.

Integration of quantitative methods and mathematical approaches for the modeling of cancer cell proliferation dynamics

Physiological processes rely on the control of cell proliferation, and the dysregulation of these processes underlies various pathological conditions, including cancer. Mathematical modeling can provide new insights into the complex regulation of cell proliferation dynamics. In this review, we first examine quantitative experimental approaches for measuring cell proliferation dynamics in vitro and compare the various types of data that can be obtained in these settings. We then explore the toolbox of common mathematical modeling frameworks that can describe cell behavior, dynamics, and interactions of proliferation. We discuss how these wet-laboratory studies may be integrated with different mathematical modeling approaches to aid the interpretation of the results and to enable the prediction of cell behaviors, specifically in the context of cancer.

Interferon-beta inhibits human glioma stem cell growth by modulating immune response and cell cycle related signaling pathways

Malignant Glioma is characterized by strong self-renewal potential and immature differentiation potential. The main reason is that malignant glioma holds key cluster cells, glioma stem cells (GSCs). GSCs contribute to tumorigenesis, tumor progression, recurrence, and treatment resistance. Interferon-beta (IFN-β) is well known for its anti-proliferative efficacy in diverse cancers. IFN-β also displayed potent antitumor effects in malignant glioma. IFN-β affect both GSCs and Neural stem cells (NSCs) in the treatment of gliomas. However, the functional comparison, similar or different effects of IFN-β on GSCs and NSCs are rarely reported. Here, we studied the similarities and differences of the responses to IFN-β between human GSCs and normal NSCs. We found that IFN-β preferentially inhibited GSCs over NSCs. The cell body and nucleus size of GSCs increased after IFN-β treatment, and the genomic analysis revealed the enrichment of the upregulated immune response, cell adhesion genes and down regulated cell cycle, ribosome pathways. Several typical cyclin genes, including cyclin A2 (CCNA2), cyclin B1 (CCNB1), cyclin B2 (CCNB2), and cyclin D1 (CCND1), were significantly downregulated in GSCs after IFN-β stimulation. We also found that continuous IFN-β stimulation after passage further enhanced the inhibitory effect. Our study revealed how genetic diversity resulted in differential effects in response to IFN-β treatment. These results may contribute to improve the applications of IFN-β in anti-cancer immunotherapy. In addition, these results may also help to design more effective pharmacological strategies to target cancer stem cells while protecting normal neural stem cells.

A pipeline for malignancy and therapy agnostic assessment of cancer drug response using cell mass measurements

Functional precision medicine offers a promising complement to genomics-based cancer therapy guidance by testing drug efficacy directly on a patient's tumor cells. Here, we describe a workflow that utilizes single-cell mass measurements with inline brightfield imaging and machine-learning based image classification to broaden the clinical utility of such functional testing for cancer. Using these image-curated mass measurements, we characterize mass response signals for 60 different drugs with various mechanisms of action across twelve different cell types, demonstrating an improved ability to detect response for several slow acting drugs as compared with standard cell viability assays. Furthermore, we use this workflow to assess drug responses for various primary tumor specimen formats including blood, bone marrow, fine needle aspirates (FNA), and malignant fluids, all with reports generated within two days and with results consistent with patient clinical responses. The combination of high-resolution measurement, broad drug and malignancy applicability, and rapid return of results offered by this workflow suggests that it is well-suited to performing clinically relevant functional assessment of cancer drug response.

What programs the size of animal cells?

The human body is programmed with definite quantities, magnitudes, and proportions. At the microscopic level, such definite sizes manifest in individual cells - different cell types are characterized by distinct cell sizes whereas cells of the same type are highly uniform in size. How do cells in a population maintain uniformity in cell size, and how are changes in target size programmed? A convergence of recent and historical studies suggest - just as a thermostat maintains room temperature - the size of proliferating animal cells is similarly maintained by homeostatic mechanisms. In this review, we first summarize old and new literature on the existence of cell size checkpoints, then discuss additional advances in the study of size homeostasis that involve feedback regulation of cellular growth rate. We further discuss recent progress on the molecules that underlie cell size checkpoints and mechanisms that specify target size setpoints. Lastly, we discuss a less-well explored teleological question: why does cell size matter and what is the functional importance of cell size control?

Eukaryotic Cell Size Control and Its Relation to Biosynthesis and Senescence

The most fundamental feature of cellular form is size, which sets the scale of all cell biological processes. Growth, form, and function are all necessarily linked in cell biology, but we often do not understand the underlying molecular mechanisms nor their specific functions. Here, we review progress toward determining the molecular mechanisms that regulate cell size in yeast, animals, and plants, as well as progress toward understanding the function of cell size regulation. It has become increasingly clear that the mechanism of cell size regulation is deeply intertwined with basic mechanisms of biosynthesis, and how biosynthesis can be scaled (or not) in proportion to cell size. Finally, we highlight recent findings causally linking aberrant cell size regulation to cellular senescence and their implications for cancer therapies.

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.

Droplet Microfluidics for High-Resolution Virology

Microfluidics has enabled a new era of cellular and molecular assays due to the small length scales, parallelization, and the modularity of various analysis and actuation functions. Droplet microfluidics, in particular, has been instrumental in providing new tools for biology with its ability to quickly and reproducibly generate drops that act as individual reactors. A notable beneficiary of this technology has been single-cell RNA sequencing, which has revealed new heterogeneities and interactions for the fundamental unit of life. However, viruses far surpass the diversity of cellular life, affect the dynamics of all ecosystems, and are a chronic source of global health crises. Despite their impact on the world, high-throughput and high-resolution viral profiling has been difficult, with conventional methods being limited to population-level averaging, large sample volumes, and few cultivable hosts. Consequently, most viruses have not been identified and studied. Droplet microfluidics holds the potential to address many of these limitations and offers new levels of sensitivity and throughput for virology. This Feature highlights recent efforts that have applied droplet microfluidics to the detection and study of viruses, including for diagnostics, virus-host interactions, and cell-independent virus assays. In combination with traditional virology methods, droplet microfluidics should prove a potent tool toward achieving a better understanding of the most abundant biological species on Earth.

Density fluctuations, homeostasis, and reproduction effects in bacteria

Single-cells grow by increasing their biomass and size. Here, we report that while mass and size accumulation rates of single Escherichia coli cells are exponential, their density and, thus, the levels of macromolecular crowding fluctuate during growth. As such, the average rates of mass and size accumulation of a single cell are generally not the same, but rather cells differentiate into increasing one rate with respect to the other. This differentiation yields a density homeostasis mechanism that we support mathematically. Further, we observe that density fluctuations can affect the reproduction rates of single cells, suggesting a link between the levels of macromolecular crowding with metabolism and overall population fitness. We detail our experimental approach and the “invisible” microfluidic arrays that enabled increased precision and throughput. Infections and natural communities start from a few cells, thus, emphasizing the significance of density-fluctuations when taking non-genetic variability into consideration.

Quantitative imaging, invisible microfluidics, and mathematical models demonstrate how the density of single E. coli cells fluctuates during the cell cycle, unmasking key homeostasis and population fitness effects.

Protein and lipid mass concentration measurement in tissues by stimulated Raman scattering microscopy

Cell mass and chemical composition are important aggregate cellular properties that are especially relevant to physiological processes, such as growth control and tissue homeostasis. Despite their importance, it has been difficult to measure these features quantitatively at the individual cell level in intact tissue. Here, we introduce normalized Raman imaging (NoRI), a stimulated Raman scattering (SRS) microscopy method that provides the local concentrations of protein, lipid, and water from live or fixed tissue samples with high spatial resolution. Using NoRI, we demonstrate that protein, lipid, and water concentrations at the single cell are maintained in a tight range in cells under the same physiological conditions and are altered in different physiological states, such as cell cycle stages, attachment to substrates of different stiffness, or by entering senescence. In animal tissues, protein and lipid concentration varies with cell types, yet an unexpected cell-to-cell heterogeneity was found in cerebellar Purkinje cells. The protein and lipid concentration profile provides means to quantitatively compare disease-related pathology, as demonstrated using models of Alzheimer’s disease. This demonstration shows that NoRI is a broadly applicable technique for probing the biological regulation of protein mass, lipid mass, and water mass for studies of cellular and tissue growth, homeostasis, and disease.

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.

Volume growth in animal cells is cell cycle dependent and shows additive fluctuations

The way proliferating animal cells coordinate the growth of their mass, volume, and other relevant size parameters is a long-standing question in biology. Studies focusing on cell mass have identified patterns of mass growth as a function of time and cell cycle phase, but little is known about volume growth. To address this question, we improved our fluorescence exclusion method of volume measurement (FXm) and obtained 1700 single-cell volume growth trajectories of HeLa cells. We find that, during most of the cell cycle, volume growth is close to exponential and proceeds at a higher rate in S-G2 than in G1. Comparing the data with a mathematical model, we establish that the cell-to-cell variability in volume growth arises from constant-amplitude fluctuations in volume steps rather than fluctuations of the underlying specific growth rate. We hypothesize that such 'additive noise' could emerge from the processes that regulate volume adaptation to biophysical cues, such as tension or osmotic pressure.

Fabricating Silicon Resonators for Analysing Biological Samples

The adaptability of microscale devices allows microtechnologies to be used for a wide range of applications. Biology and medicine are among those fields that, in recent decades, have applied microtechnologies to achieve new and improved functionality. However, despite their ability to achieve assay sensitivities that rival or exceed conventional standards, silicon-based microelectromechanical systems remain underutilised for biological and biomedical applications. Although microelectromechanical resonators and actuators do not always exhibit optimal performance in liquid due to electrical double layer formation and high damping, these issues have been solved with some innovative fabrication processes or alternative experimental approaches. This paper focuses on several examples of silicon-based resonating devices with a brief look at their fundamental sensing elements and key fabrication steps, as well as current and potential biological/biomedical applications.

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.

Functional drug susceptibility testing using single-cell mass predicts treatment outcome in patient-derived cancer neurosphere models

Functional precision medicine aims to match individual cancer patients to optimal treatment through ex vivo drug susceptibility testing on patient-derived cells. However, few functional diagnostic assays have been validated against patient outcomes at scale because of limitations of such assays. Here, we describe a high-throughput assay that detects subtle changes in the mass of individual drug-treated cancer cells as a surrogate biomarker for patient treatment response. To validate this approach, we determined ex vivo response to temozolomide in a retrospective cohort of 69 glioblastoma patient-derived neurosphere models with matched patient survival and genomics. Temozolomide-induced changes in cell mass distributions predict patient overall survival similarly to O⁶-methylguanine-DNA methyltransferase (MGMT) promoter methylation and may aid in predictions in gliomas with mismatch-repair variants of unknown significance, where MGMT is not predictive. Our findings suggest cell mass is a promising functional biomarker for cancers and drugs that lack genomic biomarkers.

Are Osteoclasts Mechanosensitive Cells?

Skeleton metabolism is a process in which osteoclasts constantly remove old bone and osteoblasts form new osteoid and induce mineralization; disruption of this balance may cause diseases. Osteoclasts play a key role in bone metabolism, as osteoclastogenesis marks the beginning of each bone remodeling cycle. As the only cell capable of bone resorption, osteoclasts are derived from the monocyte/macrophage hematopoietic precursors that terminally adhere to mineralized extracellular matrix, and they subsequently break down the extracellular compartment. Bone is generally considered the load-burdening tissue, bone homeostasis is critically affected by mechanical conductions, and the bone cells are mechanosensitive. The functions of various bone cells under mechanical forces such as chondrocytes and osteoblasts have been reported; however, the unique bone-resorbing osteoclasts are less studied. The oversuppression of osteoclasts in mechanical studies may be because of its complicated differentiation progress and flexible structure, which increases difficulty in targeting mechanical structures. This paper will focus on recent findings regarding osteoclasts and attempt to uncover proposed candidate mechanosensing structures in osteoclasts including podosome-associated complexes, gap junctions and transient receptor potential family (ion channels). We will additionally describe possible mechanotransduction signaling pathways including GTPase ras homologue family member A (RhoA), Yes-associated protein/transcriptional co-activator with PDZ-binding motif (TAZ), Ca²⁺ signaling and non-canonical Wnt signaling. According to numerous studies, evaluating the possible influence of various physical environments on osteoclastogenesis is conducive to the study of bone homeostasis.

Refractive Index Sensing for Measuring Single Cell Growth

Accessing cell growth on adhesive substrates is critical for identifying biophysical properties of cells and their therapeutic response to drug therapies. However, optical techniques have low sensitivity, and their reliability varies with cell type, whereas microfluidic technologies rely on cell suspension. In this paper, we introduced a plasmonic functional assay platform that can precisely measure cell weight and the dynamic change in real-time for adherent cells. Possessing this ability, our platform can determine growth rates of individual cells within only 10 min to map the growth profile of populations in short time intervals. The platform could successfully determine heterogeneity within the growth profile of populations and assess subpopulations exhibiting distinct growth profiles. As a proof of principle, we investigated the growth profile of MCF-7 cells and the effect of two intracellular metabolisms critical for their proliferation. We first investigated the negative effect of serum starvation on cell growth. We then studied ornithine decarboxylase (ODC) activity, a key enzyme which is involved in proliferation, and degraded under low osmolarity that inhibits cell growth. We successfully determined the significant distinction between growth profiles of MCF-7 cells and their ODC-overproducing variants that possess strong resistance to the negative effects of low osmolarity. We also demonstrated that an exogenous parameter, putrescine, could rescue cells from ODC inhibition under hypoosmotic conditions. In addition to the ability of accessing intracellular activities through ex vivo measurements, our platform could also determine therapeutic behaviors of cancer cells in response to drug treatments. Here, we investigated difluoromethylornithine (DFMO), which has antitumor effects on MCF-7 cells by inhibiting ODC activity. We successfully demonstrated the susceptibility of MCF-7 cells to such drug treatment, while its DFMO-resistant subpopulation could survive in the presence of this antigrowth agent. By rapidly determining cell growth kinetics in small samples, our plasmonic platform may be of broad use to basic research and clinical applications.

Cells under pressure

A new method for applying solid stress to aggregates of cells is shedding light on the impact of mechanical forces on cancer cells.

A Review on Theory and Modelling of Nanomechanical Sensors for Biological Applications

Over the last decades, nanomechanical sensors have received significant attention from the scientific community, as they find plenty of applications in many different research fields, ranging from fundamental physics to clinical diagnosis. Regarding biological applications, nanomechanical sensors have been used for characterizing biological entities, for detecting their presence, and for characterizing the forces and motion associated with fundamental biological processes, among many others. Thanks to the continuous advancement of micro- and nano-fabrication techniques, nanomechanical sensors have rapidly evolved towards more sensitive devices. At the same time, researchers have extensively worked on the development of theoretical models that enable one to access more, and more precise, information about the biological entities and/or biological processes of interest. This paper reviews the main theoretical models applied in this field. We first focus on the static mode, and then continue on to the dynamic one. Then, we center the attention on the theoretical models used when nanomechanical sensors are applied in liquids, the natural environment of biology. Theory is essential to properly unravel the nanomechanical sensors signals, as well as to optimize their designs. It provides access to the basic principles that govern nanomechanical sensors applications, along with their intrinsic capabilities, sensitivities, and fundamental limits of detection.

An image analysis method to survey the dynamics of polar protein abundance in the regulation of tip growth

Tip growth is critical for the lifestyle of many walled cells. In yeast and fungi, this process is typically associated with the polarized deposition of conserved tip factors, including landmarks, Rho GTPases, cytoskeleton regulators, and membrane and cell wall remodelers. Because tip growth speeds may vary extensively between life cycles or species, we asked whether the local amount of specific polar elements could determine or limit tip growth speeds. Using the model fission yeast, we developed a quantitative image analysis pipeline to dynamically correlate single tip elongation speeds and polar protein abundance in large data sets. We found that polarity landmarks are typically diluted by growth. In contrast, tip growth speed is positively correlated with the local amount of factors related to actin, secretion or cell wall remodeling, but, surprisingly, exhibits long saturation plateaus above certain concentrations of those factors. Similar saturation observed for Spitzenkörper components in much faster growing fungal hyphae suggests that elements independent of canonical surface remodelers may limit single tip growth. This work provides standardized methods and resources to decipher the complex mechanisms that control cell growth.This article has an associated First Person interview with Sarah Taheraly, joint first author of the paper.

Computationally enhanced quantitative phase microscopy reveals autonomous oscillations in mammalian cell growth

The fine balance of growth and division is a fundamental property of the physiology of cells, and one of the least understood. Its study has been thwarted by difficulties in the accurate measurement of cell size and the even greater challenges of measuring growth of a single cell over time. We address these limitations by demonstrating a computationally enhanced methodology for quantitative phase microscopy for adherent cells, using improved image processing algorithms and automated cell-tracking software. Accuracy has been improved more than twofold and this improvement is sufficient to establish the dynamics of cell growth and adherence to simple growth laws. It is also sufficient to reveal unknown features of cell growth, previously unmeasurable. With these methodological and analytical improvements, in several cell lines we document a remarkable oscillation in growth rate, occurring throughout the cell cycle, coupled to cell division or birth yet independent of cell cycle progression. We expect that further exploration with this advanced tool will provide a better understanding of growth rate regulation in mammalian cells.

Monitoring and modeling of lymphocytic leukemia cell bioenergetics reveals decreased ATP synthesis during cell division

The energetic demands of a cell are believed to increase during mitosis, but the rates of ATP synthesis and consumption during mitosis have not been quantified. Here, we monitor mitochondrial membrane potential of single lymphocytic leukemia cells and demonstrate that mitochondria hyperpolarize from the G2/M transition until the metaphase-anaphase transition. This hyperpolarization was dependent on cyclin-dependent kinase 1 (CDK1) activity. By using an electrical circuit model of mitochondria, we quantify mitochondrial ATP synthesis rates in mitosis from the single-cell time-dynamics of mitochondrial membrane potential. We find that mitochondrial ATP synthesis decreases by approximately 50% during early mitosis and increases back to G2 levels during cytokinesis. Consistently, ATP levels and ATP synthesis are lower in mitosis than in G2 in synchronized cell populations. Overall, our results provide insights into mitotic bioenergetics and suggest that cell division is not a highly energy demanding process.

ATP drives most cellular processes, although ATP production and consumption levels during mitosis remain unreported. Here, the authors combine metabolic measurements and modeling to quantify ATP levels and synthesis dynamics, revealing that ATP synthesis and consumption are lowered during mitosis.

Mapping metabolic oscillations during cell cycle progression

Proliferating cells must synthesize a wide variety of macromolecules while progressing through the cell cycle, but the coordination between cell cycle progression and cellular metabolism is still poorly understood. To identify metabolic processes that oscillate over the cell cycle, we performed comprehensive, non-targeted liquid chromatography-high resolution mass spectrometry (LC-HRMS) based metabolomics of HeLa cells isolated in the G₁ and SG₂M cell cycle phases, capturing thousands of diverse metabolite ions. When accounting for increased total metabolite abundance due to cell growth throughout the cell cycle, 18% of the observed LC-HRMS peaks were at least twofold different between the stages, consistent with broad metabolic remodeling throughout the cell cycle. While most amino acids, phospholipids, and total ribonucleotides were constant across cell cycle phases, consistent with the view that total macromolecule synthesis does not vary across the cell cycle, certain metabolites were oscillating. For example, ribonucleotides were highly phosphorylated in SG₂M, indicating an increase in energy charge, and several phosphatidylinositols were more abundant in G₁, possibly indicating altered membrane lipid signaling. Within carbohydrate metabolism, pentose phosphates and methylglyoxal metabolites were associated with the cycle. Interestingly, hundreds of yet uncharacterized metabolites similarly oscillated between cell cycle phases, suggesting previously unknown metabolic activities that may be synchronized with cell cycle progression, providing an important resource for future studies.

Modeling homeostasis mechanisms that set the target cell size

How organisms maintain cell size homeostasis is a long-standing problem that remains unresolved, especially in multicellular organisms. Recent experiments in diverse animal cell types demonstrate that within a cell population, cellular proliferation is low for small and large cells, but high at intermediate sizes. Here we use mathematical models to explore size-control strategies that drive such a non-monotonic profile resulting in the proliferation capacity being maximized at a target cell size. Our analysis reveals that most models of size control yield proliferation capacities that vary monotonically with cell size, and non-monotonicity requires two key mechanisms: (1) the growth rate decreases with increasing size for excessively large cells; and (2) cell division occurs as per the Adder model (division is triggered upon adding a fixed size from birth), or a Sizer-Adder combination. Consistent with theory, Jurkat T cell growth rates increase with size for small cells, but decrease with size for large cells. In summary, our models show that regulation of both growth and cell-division timing is necessary for size control in animal cells, and this joint mechanism leads to a target cell size where cellular proliferation capacity is maximized.

Mass measurements during lymphocytic leukemia cell polyploidization decouple cell cycle- and cell size-dependent growth

Cell size is believed to influence cell growth through limited transport efficiency in larger cells. However, this has not been experimentally investigated due to a lack of noninvasive, high-precision growth quantification methods suitable for measuring large cells. Here, we have engineered large versions of microfluidic mass sensors called suspended microchannel resonators in order to study the growth of single mammalian cells that range 100-fold in mass. Our measurements, which decouple growth effects caused by cell cycle and cell size, revealed that absolute cell size does not impose strict transport or other limitations that would inhibit growth and that cell cycle has a large influence on growth.

Cell size is believed to influence cell growth and metabolism. Consistently, several studies have revealed that large cells have lower mass accumulation rates per unit mass (i.e., growth efficiency) than intermediate-sized cells in the same population. Size-dependent growth is commonly attributed to transport limitations, such as increased diffusion timescales and decreased surface-to-volume ratio. However, separating cell size- and cell cycle-dependent growth is challenging. To address this, we monitored growth efficiency of pseudodiploid mouse lymphocytic leukemia cells during normal proliferation and polyploidization. This was enabled by the development of large-channel suspended microchannel resonators that allow us to monitor buoyant mass of single cells ranging from 40 pg (small pseudodiploid cell) to over 4,000 pg, with a resolution ranging from ∼1% to ∼0.05%. We find that cell growth efficiency increases, plateaus, and then decreases as cell cycle proceeds. This growth behavior repeats with every endomitotic cycle as cells grow into polyploidy. Overall, growth efficiency changes 33% throughout the cell cycle. In contrast, increasing cell mass by over 100-fold during polyploidization did not change growth efficiency, indicating exponential growth. Consistently, growth efficiency remained constant when cell cycle was arrested in G₂. Thus, cell cycle is a primary determinant of growth efficiency. As growth remains exponential over large size scales, our work finds no evidence for transport limitations that would decrease growth efficiency.

On the Molecular Mechanisms Regulating Animal Cell Size Homeostasis

Cell size is fundamental to cell physiology because it sets the scale of intracellular geometry, organelles, and biosynthetic processes. In animal cells, size homeostasis is controlled through two phenomenologically distinct mechanisms. First, size-dependent cell cycle progression ensures that smaller cells delay cell cycle progression to accumulate more biomass than larger cells prior to cell division. Second, size-dependent cell growth ensures that larger and smaller cells grow slower per unit mass than more optimally sized cells. This decade has seen dramatic progress in single-cell technologies establishing the diverse phenomena of cell size control in animal cells. Here, we review this recent progress and suggest pathways forward to determine the underlying molecular mechanisms.

Differential Scaling of Gene Expression with Cell Size May Explain Size Control in Budding Yeast

Yeast cells must grow to a critical size before committing to division. It is unknown how size is measured. We find that as cells grow, mRNAs for some cell-cycle activators scale faster than size, increasing in concentration, while mRNAs for some inhibitors scale slower than size, decreasing in concentration. Size-scaled gene expression could cause an increasing ratio of activators to inhibitors with size, triggering cell-cycle entry. Consistent with this, expression of the CLN2 activator from the promoter of the WHI5 inhibitor, or vice versa, interfered with cell size homeostasis, yielding a broader distribution of cell sizes. We suggest that size homeostasis comes from differential scaling of gene expression with size. Differential regulation of gene expression as a function of cell size could affect many cellular processes.

A G1 Sizer Coordinates Growth and Division in the Mouse Epidermis

Cell size homeostasis is often achieved by coupling cell-cycle progression to cell growth. Growth has been shown to drive cell-cycle progression in bacteria and yeast through "sizers," wherein cells of varying birth size divide at similar final sizes [1-3], and "adders," wherein cells increase in size a fixed amount per cell cycle [4-6]. Intermediate control phenomena are also observed, and even the same organism can exhibit different control phenomena depending on growth conditions [2, 7, 8]. Although studying unicellular organisms in laboratory conditions may give insight into their growth control in the wild, this is less apparent for studies of mammalian cells growing outside the organism. Sizers, adders, and intermediate phenomena have been observed in vitro [9-12], but it is unclear how this relates to mammalian cell proliferation in vivo. To address this question, we analyzed time-lapse images of the mouse epidermis taken over 1 week during normal tissue turnover [13]. We quantified the 3D volume growth and cell-cycle progression of single cells within the mouse skin. In dividing epidermal stem cells, we found that cell growth is coupled to division through a sizer operating largely in the G1 phase of the cell cycle. Thus, although the majority of tissue culture studies have identified adders, our analysis demonstrates that sizers are important in vivo and highlights the need to determine their underlying molecular origin.

Dependence of fluorodeoxyglucose (FDG) uptake on cell cycle and dry mass: a single-cell study using a multi-modal radiography platform

High glucose uptake by cancer compared to normal tissues has long been utilized in fluorodeoxyglucose-based positron emission tomography (FDG-PET) as a contrast mechanism. The FDG uptake rate has been further related to the proliferative potential of cancer, specifically the proliferation index (PI) - the proportion of cells in S, G2 or M phases. The underlying hypothesis was that the cells preparing for cell division would consume more energy and metabolites as building blocks for biosynthesis. Despite the wide clinical use, mixed reports exist in the literature on the relationship between FDG uptake and PI. This may be due to the large variation in cancer types or methods adopted for the measurements. Of note, the existing methods can only measure the average properties of a tumor mass or cell population with highly-heterogeneous constituents. In this study, we have built a multi-modal live-cell radiography system and measured the [18F]FDG uptake by single HeLa cells together with their dry mass and cell cycle phase. The results show that HeLa cells take up twice more [18F]FDG in S, G2 or M phases than in G1 phase, which confirms the association between FDG uptake and PI at a single-cell level. Importantly, we show that [18F]FDG uptake and cell dry mass have a positive correlation in HeLa cells, which suggests that high [18F]FDG uptake in S, G2 or M phases can be largely attributed to increased dry mass, rather than the activities preparing for cell division. This interpretation is consistent with recent observations that the energy required for the preparation of cell division is much smaller than that for maintaining house-keeping proteins.

Microfluidic Single-Cell Analytics

What is the impact of cellular heterogeneity on process performance? How do individual cells contribute to averaged process productivity? Single-cell analysis is a key technology for answering such key questions of biotechnology, beyond bulky measurements with populations. The analysis of cellular individuality, its origins, and the dependency of process performance on cellular heterogeneity has tremendous potential for optimizing biotechnological processes in terms of metabolic, reaction, and process engineering. Microfluidics offer unmatched environmental control of the cellular environment and allow massively parallelized cultivation of single cells. However, the analytical accessibility to a cell's physiology is of crucial importance for obtaining the desired information on the single-cell production phenotype. Highly sensitive analytics are required to detect and quantify the minute amounts of target analytes and small physiological changes in a single cell. For their application to biotechnological questions, single-cell analytics must evolve toward the measurement of kinetics and specific rates of the smallest catalytic unit, the single cell. In this chapter, we focus on an introduction to the latest single-cell analytics and their application for obtaining physiological parameters in a biotechnological context from single cells. We present and discuss recent advancements in single-cell analytics that enable the analysis of cell-specific growth, uptake, and production kinetics, as well as the gene expression and regulatory mechanisms at a single-cell level.

Mechano-Optical Analysis of Single Cells with Transparent Microcapillary Resonators

The study of biophysical properties of single cells is becoming increasingly relevant in cell biology and pathology. The measurement and tracking of magnitudes such as cell stiffness, morphology, and mass or refractive index have brought otherwise inaccessible knowledge about cell physiology, as well as innovative methods for high-throughput label-free cell classification. In this work, we present hollow resonator devices based on suspended glass microcapillaries for the simultaneous measurement of single-cell buoyant mass and reflectivity with a throughput of 300 cells/minute. In the experimental methodology presented here, both magnitudes are extracted from the devices' response to a single probe, a focused laser beam that enables simultaneous readout of changes in resonance frequency and reflected optical power of the devices as cells flow within them. Through its application to MCF-7 human breast adenocarcinoma cells and MCF-10A nontumorigenic cells, we demonstrate that this mechano-optical technique can successfully discriminate pathological from healthy cells of the same tissue type.

Micropipette Resonator Enabling Targeted Aspiration and Mass Measurement of Single Particles and Cells

This paper reports micropipette resonators, mechanical resonator-integrated micropipettes, which enable selective aspiration and mass measurement of particles or cells suspended in liquids with two orthogonal vibration modes. A custom pipette pulling system is built to provide power-modulated linear heating on a rotating glass capillary to make an asymmetric cross section with extended uniformity.A glass capillary is stretched with the custom puller, cut within the pulled region, polished, mounted on a machined metallic jig, and then coated with a metal. As a result, a doubly clamped tube resonator-integrated micropipette is made. For simultaneous frequency readouts of two orthogonal modes, an optical pickup, originally developed for optical data storage, is configured closely above and properly aligned to the micropipette resonator and two digital phase-locked loops are employed. For mass responsivity calibration, frequency shifts of the micropipette resonator are measured with various liquids and glass microparticles. Buoyant masses of unicellular organisms, Paramecium aurelia, freely swimming in a culture dish are successfully measured with two orthogonal modes.

Trisomy of a Down Syndrome Critical Region Globally Amplifies Transcription via HMGN1 Overexpression

Down syndrome (DS, trisomy 21) is associated with developmental abnormalities and increased leukemia risk. To reconcile chromatin alterations with transcriptome changes, we performed paired exogenous spike-in normalized RNA and chromatin immunoprecipitation sequencing in DS models. Absolute normalization unmasks global amplification of gene expression associated with trisomy 21. Overexpression of the nucleosome binding protein HMGN1 (encoded on chr21q22) recapitulates transcriptional changes seen with triplication of a Down syndrome critical region on distal chromosome 21, and HMGN1 is necessary for B cell phenotypes in DS models. Absolute exogenous-normalized chromatin immunoprecipitation sequencing (ChIP-Rx) also reveals a global increase in histone H3K27 acetylation caused by HMGN1. Transcriptional amplification downstream of HMGN1 is enriched for stage-specific programs of B cells and B cell acute lymphoblastic leukemia, dependent on the developmental cellular context. These data offer a mechanistic explanation for DS transcriptional patterns and suggest that further study of HMGN1 and RNA amplification in diverse DS phenotypes is warranted.

How trisomy 21 contributes to Down syndrome phenotypes, including increased leukemia risk, is not well understood. Mowery et al. use per-cell normalization approaches to reveal global transcriptional amplification in Down syndrome models. HMGN1 overexpression is sufficient to induce these alterations and promotes lineage-associated transcriptional programs, signaling, and B cell progenitor phenotypes.

Cell Size Control in Plants

The genetic control of the characteristic cell sizes of different species and tissues is a long-standing enigma. Plants are convenient for studying this question in a multicellular context, as their cells do not move and are easily tracked and measured from organ initiation in the meristems to subsequent morphogenesis and differentiation. In this article, we discuss cell size control in plants compared with other organisms. As seen from yeast cells to mammalian cells, size homeostasis is maintained cell autonomously in the shoot meristem. In developing organs, vacuolization contributes to cell size heterogeneity and may resolve conflicts between growth control at the cellular and organ levels. Molecular mechanisms for cell size control have implications for how cell size responds to changes in ploidy, which are particularly important in plant development and evolution. We also discuss comparatively the functional consequences of cell size and their potential repercussions at higher scales, including genome evolution.