Live-cell mass profiling: an emerging approach in quantitative biophysics

Tracking of lineage mass via quantitative phase imaging and confinement in low refractive index microwells

Measurements of cell lineages are central to a variety of fundamental biological questions, ranging from developmental to cancer biology. However, accurate lineage tracing requires nearly perfect cell tracking, which can be challenging due to cell motion during imaging. Here we demonstrate the integration of microfabrication, imaging, and image processing approaches to demonstrate a platform for cell lineage tracing. We use quantitative phase imaging (QPI), a label-free imaging approach that quantifies cell mass. This gives an additional parameter, cell mass, that can be used to improve tracking accuracy. We confine lineages within microwells fabricated to reduce cell adhesion to sidewalls made of a low refractive index polymer. This also allows the microwells themselves to serve as references for QPI, enabling measurement of cell mass even in confluent microwells. We demonstrate application of this approach to immortalized adherent and nonadherent cell lines as well as stimulated primary B cells cultured ex vivo. Overall, our approach enables lineage tracking, or measurement of lineage mass, in a platform that can be customized to varied cell types.

Quadrant darkfield (QDF) for label-free imaging of intracellular puncta

Significance

Measuring changes in cellular structure and organelles is crucial for understanding disease progression and cellular responses to treatments. A label-free imaging method can aid in advancing biomedical research and therapeutic strategies.

Aim

This study introduces a computational darkfield imaging approach named quadrant darkfield (QDF) to separate smaller cellular features from large structures, enabling label-free imaging of cell organelles and structures in living cells.

Approach

Using a programmable LED array as illumination source, we vary the direction of illumination to encode additional information about the feature size within cells. This is possible due to the varying level of directional scattering produced by features based on their sizes relative to the wavelength of light used.

Results

QDF successfully resolved small cellular features without interference from larger structures. QDF signal is more consistent during cell shape changes than traditional darkfield. QDF signals correlate with flow cytometry side scatter measurements, effectively differentiating cells by organelle content.

Conclusions

QDF imaging enhances the study of subcellular structures in living cells, offering improved quantification of organelle content compared to darkfield without labels. This method can be simultaneously performed with other techniques such as quantitative phase imaging to generate a multidimensional picture of living cells in real-time.

Sub-Nanogram Resolution Measurement of Inertial Mass and Density Using Magnetic-Field-Guided Bubble Microthruster

Artificial micro/nanomotors using active particles hold vast potential in applications such as drug delivery and microfabrication. However, upgrading them to micro/nanorobots capable of performing precise tasks with sophisticated functions remains challenging. Bubble microthruster (BMT) is introduced, a variation of the bubble-driven microrobot, which focuses the energy from a collapsing microbubble to create an inertial impact on nearby target microparticles. Utilizing ultra-high-speed imaging, the microparticle mass and density is determined with sub-nanogram resolution based on the relaxation time characterizing the microparticle's transient response. Master curves of the BMT method are shown to be dependent on the viscosity of the solution. The BMT, controlled by a gamepad with magnetic-field guidance, precisely manipulates target microparticles, including bioparticles. Validation involves measuring the polystyrene microparticle mass and hollow glass microsphere density, and assessing the mouse embryo mass densities. The BMT technique presents a promising chip-free, real-time, highly maneuverable strategy that integrates bubble microrobot-based manipulation with precise bioparticle mass and density detection, which can facilitate microscale bioparticle characterizations such as embryo growth monitoring.

Label-free three-dimensional imaging and quantitative analysis of living fibroblasts and myofibroblasts by holotomographic microscopy

Holotomography (HT) is a cutting-edge fast live-cell quantitative label-free imaging technique. Based on the principle of quantitative phase imaging, it combines holography and tomography to record a three-dimensional map of the refractive index, used as intrinsic optical and quantitative imaging contrast parameter of biological samples, at a sub-micrometer spatial resolution. In this study HT has been employed for the first time to analyze the changes of fibroblasts differentiating towards myofibroblasts - recognized as the main cell player of fibrosis - when cultured in vitro with the pro-fibrotic factor, namely transforming growth factor-β1. In parallel, F-actin, vinculin, α-smooth muscle actin, phospho-myosin light chain 2, type-1 collagen, peroxisome proliferator-activated receptor-gamma coactivator-1α expression and mitochondria were evaluated by confocal laser scanning microscopy. Plasmamembrane passive properties and transient receptor potential canonical channels' currents were also recorded by whole-cell patch-clamp. The fluorescence images and electrophysiological results have been compared to the data obtained by HT and their congruence has been discussed. HT turned out to be a valid approach to morphologically distinguish fibroblasts from well differentiated myofibroblasts while obtaining objective measures concerning volume, surface area, projection area, surface index and dry mass (i.e., the mass of the non-aqueous content inside the cell including proteins and subcellular organelles) of the entire cell, nuclei and nucleoli with the major advantage to monitor outer and inner features in living cells in a non-invasive, rapid and label-free approach. HT might open up new research opportunities in the field of fibrotic diseases. RESEARCH HIGHLIGHTS: Holotomography (HT) is a label-free laser interferometric imaging technology exploiting the intrinsic optical property of cells namely refractive index (RI) to enable a direct imaging and analysis of whole cells or intracellular organelles. HT turned out a valid approach to distinguish morphological features of living unlabeled fibroblasts from differentiated myofibroblasts. HT provided quantitative information concerning volume, surface area, projection area, surface index and dry mass of the entire fibroblasts/myofibroblasts, nuclei and nucleoli.

Receptor tyrosine kinase inhibition leads to regression of acral melanoma by targeting the tumor microenvironment

Acral melanoma (AM) is an aggressive melanoma variant that arises from palmar, plantar, and nail unit melanocytes. Compared to non-acral cutaneous melanoma (CM), AM is biologically distinct, has an equal incidence across genetic ancestries, typically presents in advanced stage disease, is less responsive to therapy, and has an overall worse prognosis. Independent analysis of published genomic and transcriptomic sequencing identified that receptor tyrosine kinase (RTK) ligands and adapter proteins are frequently amplified, translocated, and/or overexpressed in AM. To target these unique genetic changes, a zebrafish acral melanoma model was exposed to a panel of narrow and broad spectrum multi-RTK inhibitors, revealing that dual FGFR/VEGFR inhibitors decrease acral-analogous melanocyte proliferation and migration. The potent pan-FGFR/VEGFR inhibitor, Lenvatinib, uniformly induces tumor regression in AM patient-derived xenograft (PDX) tumors but only slows tumor growth in CM models. Unlike other multi-RTK inhibitors, Lenvatinib is not directly cytotoxic to dissociated AM PDX tumor cells and instead disrupts tumor architecture and vascular networks. Considering the great difficulty in establishing AM cell culture lines, these findings suggest that AM may be more sensitive to microenvironment perturbations than CM. In conclusion, dual FGFR/VEGFR inhibition may be a viable therapeutic strategy that targets the unique biology of AM.

Perspective on quantitative phase imaging to improve precision cancer medicine

Significance

Quantitative phase imaging (QPI) offers a label-free approach to non-invasively characterize cellular processes by exploiting their refractive index based intrinsic contrast. QPI captures this contrast by translating refractive index associated phase shifts into intensity-based quantifiable data with nanoscale sensitivity. It holds significant potential for advancing precision cancer medicine by providing quantitative characterization of the biophysical properties of cells and tissue in their natural states.

Aim

This perspective aims to discuss the potential of QPI to increase our understanding of cancer development and its response to therapeutics. It also explores new developments in QPI methods towards advancing personalized cancer therapy and early detection.

Approach

We begin by detailing the technical advancements of QPI, examining its implementations across transmission and reflection geometries and phase retrieval methods, both interferometric and non-interferometric. The focus then shifts to QPI's applications in cancer research, including dynamic cell mass imaging for drug response assessment, cancer risk stratification, and in-vivo tissue imaging.

Results

QPI has emerged as a crucial tool in precision cancer medicine, offering insights into tumor biology and treatment efficacy. Its sensitivity to detecting nanoscale changes holds promise for enhancing cancer diagnostics, risk assessment, and prognostication. The future of QPI is envisioned in its integration with artificial intelligence, morpho-dynamics, and spatial biology, broadening its impact in cancer research.

Conclusions

QPI presents significant potential in advancing precision cancer medicine and redefining our approach to cancer diagnosis, monitoring, and treatment. Future directions include harnessing high-throughput dynamic imaging, 3D QPI for realistic tumor models, and combining artificial intelligence with multi-omics data to extend QPI's capabilities. As a result, QPI stands at the forefront of cancer research and clinical application in cancer care.

Engineering water exchange is a safe and effective method for magnetic resonance imaging in diverse cell types

Aquaporin-1 (Aqp1), a water channel, has garnered significant interest for cell-based medicine and in vivo synthetic biology due to its ability to be genetically encoded to produce magnetic resonance signals by increasing the rate of water diffusion in cells. However, concerns regarding the effects of Aqp1 overexpression and increased membrane diffusivity on cell physiology have limited its widespread use as a deep-tissue reporter. In this study, we present evidence that Aqp1 generates strong diffusion-based magnetic resonance signals without adversely affecting cell viability or morphology in diverse cell lines derived from mice and humans. Our findings indicate that Aqp1 overexpression does not induce ER stress, which is frequently associated with heterologous expression of membrane proteins. Furthermore, we observed that Aqp1 expression had no detrimental effects on native biological activities, such as phagocytosis, immune response, insulin secretion, and tumor cell migration in the analyzed cell lines. These findings should serve to alleviate any lingering safety concerns regarding the utilization of Aqp1 as a genetic reporter and should foster its broader application as a noninvasive reporter for in vivo studies.

LVING reveals the intracellular structure of cell growth

The continuous balance of growth and degradation inside cells maintains homeostasis. Disturbance of this balance by internal or external factors cause state of disease, while effective disease treatments seek to restore this balance. Here, we present a method based on quantitative phase imaging (QPI) based measurements of cell mass and the velocity of mass transport to quantify the balance of growth and degradation within intracellular control volumes. The result, which we call Lagrangian velocimetry for intracellular net growth (LVING), provides high resolution maps of intracellular biomass production and degradation. We use LVING to quantify the growth in different regions of the cell during phases of the cell cycle. LVING can also be used to quantitatively compare the effect of range of chemotherapy drug doses on subcellular growth processes. Finally, we applied LVING to characterize the effect of autophagy on the growth machinery inside cells. Overall, LVING reveals both the structure and distribution of basal growth within cells, as well as the disruptions to this structure that occur during alterations in cell state.

Single-shot quantitative phase-fluorescence imaging using cross-grating wavefront microscopy

The article introduces an optical microscopy technique capable of simultaneously acquiring quantitative fluorescence and phase (or equivalently wavefront) images with a single camera sensor, avoiding any delay between both images, or registration of images acquired separately. The method is based on the use of a 2-dimensional diffraction grating (aka cross-grating) positioned at a millimeter distance from a 2-color camera. Fluorescence and wavefront images are extracted from the two color channels of the camera, and retrieved by image demodulation. The applicability of the method is illustrated on various samples, namely fluorescent micro-beads, bacteria and mammalian cells.

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.

Measuring Drug Response with Single-Cell Growth Rate Quantification

Intratumoral heterogeneity is a substantial cause of drug resistance development during chemotherapy or other drug treatments for cancer. Therefore, monitoring and measuring cell exposure and response to drugs at the single-cell level are crucial. Previous research suggested that the single-cell growth rate can be used to investigate drug-cell interactions. However, currently established methods for quantifying single-cell growth are limited to isolated or monolayer cells. Here, we introduce a technique that accurately measures both 2D and 3D cell growth rates using label-free ratiometric stimulated Raman scattering (SRS) microscopy. We use deuterated amino acids, leucine, isoleucine, and valine, as tracers and measure the C-D SRS signal from deuterium-labeled proteins and the C-H SRS signal from unlabeled proteins simultaneously to determine the cell growth rate at the single-cell level. The technique offers single-cell level drug sensitivity measurement with a shorter turnaround time (within 12 h) than most traditional assays. The submicrometer resolution of the imaging technique allows us to examine the effects of chemotherapeutic drugs, including kinase inhibitors, mitotic inhibitors, and topoisomerase II inhibitors, on both the cell growth rate and morphology. The capability of quantifying 3D cell growth rates provides insight into a deeper understanding of the cell-drug interaction in the actual tumor environment.

Dielectric Metasurface Enabled Compact, Single-Shot Digital Holography for Quantitative Phase Imaging

Quantitative phase imaging (QPI) enables nondestructive, real-time, label-free imaging of transparent specimens and can reveal information about their fundamental properties such as cell size and morphology, mass density, particle dynamics, and cellular fluctuations. Development of high-performance and low-cost quantitative phase imaging systems is thus required in many fields, including on-site biomedical imaging and industrial inspection. Here, we propose an ultracompact, highly stable interferometer based on a single-layer dielectric metasurface for common path off-axis digital holography and experimentally demonstrate quantitative phase imaging. The interferometric imaging system leveraging an ultrathin multifunctional metasurface captures image plane holograms in a single shot and provides quantitative phase information on the test samples for extraction of its physical properties. With the benefits of planar engineering and high integrability, the proposed metasurface-based method establishes a stable miniaturized QPI system for reliable and cost-effective point-of-care devices, live cell imaging, 3D topography, and edge detection for optical computing.

Engineering water exchange is a safe and effective method for magnetic resonance imaging in diverse cell types

Aquaporin-1 (Aqp1), a water channel, has garnered significant interest for cell-based medicine and in vivo synthetic biology due to its ability to be genetically encoded to produce magnetic resonance signals by increasing the rate of water diffusion in cells. However, concerns regarding the effects of Aqp1 overexpression and increased membrane diffusivity on cell physiology have limited its widespread use as a deep-tissue reporter. In this study, we present evidence that Aqp1 generates strong diffusion-based magnetic resonance signals without adversely affecting cell viability or morphology in diverse cell lines derived from mice and humans. Our findings indicate that Aqp1 overexpression does not induce ER stress, which is frequently associated with heterologous expression of membrane proteins. Furthermore, we observed that Aqp1 expression had no detrimental effects on native biological activities, such as phagocytosis, immune response, insulin secretion, and tumor cell migration in the analyzed cell lines. These findings should serve to alleviate any lingering safety concerns regarding the utilization of Aqp1 as a genetic reporter and should foster its broader application as a noninvasive reporter for in vivo studies.

Hybrid machine-learning framework for volumetric segmentation and quantification of vacuoles in individual yeast cells using holotomography

The precise, quantitative evaluation of intracellular organelles in three-dimensional (3D) imaging data poses a significant challenge due to the inherent constraints of traditional microscopy techniques, the requirements of the use of exogenous labeling agents, and existing computational methods. To counter these challenges, we present a hybrid machine-learning framework exploiting correlative imaging of 3D quantitative phase imaging with 3D fluorescence imaging of labeled cells. The algorithm, which synergistically integrates a random-forest classifier with a deep neural network, is trained using the correlative imaging data set, and the trained network is then applied to 3D quantitative phase imaging of cell data. We applied this method to live budding yeast cells. The results revealed precise segmentation of vacuoles inside individual yeast cells, and also provided quantitative evaluations of biophysical parameters, including volumes, concentration, and dry masses of automatically segmented vacuoles.

Dry mass photometry of single bacteria using quantitative wavefront microscopy

Quantitative phase microscopy (QPM) represents a noninvasive alternative to fluorescence microscopy for cell observation with high contrast and for the quantitative measurement of dry mass (DM) and growth rate at the single-cell level. While DM measurements using QPM have been widely conducted on mammalian cells, bacteria have been less investigated, presumably due to the high resolution and high sensitivity required by their smaller size. This article demonstrates the use of cross-grating wavefront microscopy, a high-resolution and high-sensitivity QPM, for accurate DM measurement and monitoring of single microorganisms (bacteria and archaea). The article covers strategies for overcoming light diffraction and sample focusing, and introduces the concepts of normalized optical volume and optical polarizability (OP) to gain additional information beyond DM. The algorithms for DM, optical volume, and OP measurements are illustrated through two case studies: monitoring DM evolution in a microscale colony-forming unit as a function of temperature, and using OP as a potential species-specific signature.

Dynamic full-field optical coherence tomography for live-cell imaging and growth-phase monitoring in Aspergillus fumigatus

Introduction

The diagnosis of cutaneous manifestations of deep mycoses relies on both histopathological and direct examinations. Yet, the current diagnostic criteria cannot prevent missed cases, including invasive aspergillosis, which requires the development of a novel diagnostic approach and imaging tools. We recently introduced the use of dynamic full-field optical coherence tomography (D-FF-OCT) in fungal diagnostics with a definition approaching that of conventional microscopy and the ability to return metabolic information regarding different fungal species. The present work focuses on subcellular dynamics and live-cell imaging of Aspergillus fumigatus with D-FF-OCT to follow the fungal growth stages.

Methods

The A. fumigatus ATCC 204305 quality-control strain was used for all imaging experiments, following incubation times varying between 24 and 72 h at 30°C in a humidified chamber on Sabouraud dextrose agar. Fungal growth was subsequently monitored with D-FF-OCT for up to 5 h at room temperature and following the pharmacological stress of either voriconazole, amphotericin B, or caspofungin gradient concentration.

Results

D-FF-OCT images allow not only the visualization of intracellular trafficking of vacuoles but also an evolving dynamic segmentation of conidiophores depending on the chronological development and aging of the hyphae or the effect of antifungal treatment. The same applies to conidial heads, with the most intense D-FF-OCT signal coming from vesicles, revealing a changing dynamic within a few hours only, as well as complete extinction following subsequent drying of the Sabouraud dextrose agar.

Discussion

These results provide additional data on the ability of D-FF-OCT to monitor some of the main life cycle processes, dynamics, and intracellular trafficking of vacuoles in A. fumigatus, with or without the effect of pharmacological stress. Such complementary metabolic information could help both clinicians and microbiologists in either mechanistic studies toward experimental mycology or the development of a potential D-FF-OCT-guided diagnosis of superficial fungal infections.

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.

Drug screening at single-organoid resolution via bioprinting and interferometry

High throughput drug screening is an established approach to investigate tumor biology and identify therapeutic leads. Traditional platforms use two-dimensional cultures which do not accurately reflect the biology of human tumors. More clinically relevant model systems such as three-dimensional tumor organoids can be difficult to scale and screen. Manually seeded organoids coupled to destructive endpoint assays allow for the characterization of treatment response, but do not capture transitory changes and intra-sample heterogeneity underlying clinically observed resistance to therapy. We present a pipeline to generate bioprinted tumor organoids linked to label-free, time-resolved imaging via high-speed live cell interferometry (HSLCI) and machine learning-based quantitation of individual organoids. Bioprinting cells gives rise to 3D structures with unaltered tumor histology and gene expression profiles. HSLCI imaging in tandem with machine learning-based segmentation and classification tools enables accurate, label-free parallel mass measurements for thousands of organoids. We demonstrate that this strategy identifies organoids transiently or persistently sensitive or resistant to specific therapies, information that could be used to guide rapid therapy selection.

RNA-mediated demixing transition of low-density condensates

Biomolecular condensates play a key role in organizing cellular reactions by concentrating a specific set of biomolecules. However, whether condensate formation is accompanied by an increase in the total mass concentration within condensates or by the demixing of already highly crowded intracellular components remains elusive. Here, using refractive index imaging, we quantify the mass density of several condensates, including nucleoli, heterochromatin, nuclear speckles, and stress granules. Surprisingly, the latter two condensates exhibit low densities with a total mass concentration similar to the surrounding cyto- or nucleoplasm. Low-density condensates display higher permeability to cellular protein probes. We find that RNA tunes the biomolecular density of condensates. Moreover, intracellular structures such as mitochondria heavily influence the way phase separation proceeds, impacting the localization, morphology, and growth of condensates. These findings favor a model where segregative phase separation driven by non-associative or repulsive molecular interactions together with RNA-mediated selective association of specific components can give rise to low-density condensates in the crowded cellular environment.

Voltage-dependent volume regulation controls epithelial cell extrusion and morphology

Epithelial cells work collectively to provide a protective barrier, yet also turn over rapidly by cell death and division. If the number of dying cells does not match those dividing, the barrier would vanish, or tumors can form. Mechanical forces and the stretch-activated ion channel (SAC) Piezo1 link both processes; stretch promotes cell division and crowding triggers cell death by initiating live cell extrusion1,2. However, it was not clear how particular cells within a crowded region are selected for extrusion. Here, we show that individual cells transiently shrink via water loss before they extrude. Artificially inducing cell shrinkage by increasing extracellular osmolarity is sufficient to induce cell extrusion. Pre-extrusion cell shrinkage requires the voltage-gated potassium channels Kv1.1 and Kv1.2 and the chloride channel SWELL1, upstream of Piezo1. Activation of these voltage-gated channels requires the mechano-sensitive Epithelial Sodium Channel, ENaC, acting as the earliest crowd-sensing step. Imaging with a voltage dye indicated that epithelial cells lose membrane potential as they become crowded and smaller, yet those selected for extrusion are markedly more depolarized than their neighbours. Loss of any of these channels in crowded conditions causes epithelial buckling, highlighting an important role for voltage and water regulation in controlling epithelial shape as well as extrusion. Thus, ENaC causes cells with similar membrane potentials to slowly shrink with compression but those with reduced membrane potentials to be eliminated by extrusion, suggesting a chief driver of cell death stems from insufficient energy to maintain cell membrane potential.

Transferred mitochondria accumulate reactive oxygen species, promoting proliferation

Recent studies reveal that lateral mitochondrial transfer, the movement of mitochondria from one cell to another, can affect cellular and tissue homeostasis. Most of what we know about mitochondrial transfer stems from bulk cell studies and have led to the paradigm that functional transferred mitochondria restore bioenergetics and revitalize cellular functions to recipient cells with damaged or non-functional mitochondrial networks. However, we show that mitochondrial transfer also occurs between cells with functioning endogenous mitochondrial networks, but the mechanisms underlying how transferred mitochondria can promote such sustained behavioral reprogramming remain unclear. We report that unexpectedly, transferred macrophage mitochondria are dysfunctional and accumulate reactive oxygen species in recipient cancer cells. We further discovered that reactive oxygen species accumulation activates ERK signaling, promoting cancer cell proliferation. Pro-tumorigenic macrophages exhibit fragmented mitochondrial networks, leading to higher rates of mitochondrial transfer to cancer cells. Finally, we observe that macrophage mitochondrial transfer promotes tumor cell proliferation in vivo. Collectively these results indicate that transferred macrophage mitochondria activate downstream signaling pathways in a ROS-dependent manner in cancer cells, and provide a model of how sustained behavioral reprogramming can be mediated by a relatively small amount of transferred mitochondria in vitro and in vivo.

Fabrication and validation of an LED array microscope for multimodal, quantitative imaging

The combination of multiple imaging modalities in a single microscopy system can enable new insights into biological processes. In this work, we describe the construction and rigorous characterization of a custom microscope with multimodal imaging in a single, cost-effective system. Our design utilizes advances in LED technology, robotics, and open-source software, along with existing optical components and precision optomechanical parts to offer a modular and versatile design. This microscope is operated using software written in Arduino and Python and has the ability to run multi-day automated imaging experiments when placed inside of a cell culture incubator. Additionally, we provide and demonstrate methods to validate images taken in brightfield and darkfield, along with validation and optimization for differential phase contrast (DPC) quantitative phase imaging.

Reduction in required volume of imaging data and image reconstruction time for adaptive-illumination Fourier ptychographic microscopy

Fourier ptychographic microscopy (FPM) is a promising super-resolution computational imaging technology. It stitches a series of low-resolution (LR) images in the Fourier domain by an iterative method. Thus, it obtains a large field of view and high-resolution quantitative phase images. Owing to its capability to perform high-spatial bandwidth product imaging, FPM is widely used in the reconstruction of conventional static samples. However, the influence of the FPM imaging mechanism limits its application in high-speed dynamic imaging. To solve this problem, an adaptive-illumination FPM scheme using regional energy estimation is proposed. Starting with several captured real LR images, the energy distribution of all LR images is estimated, and select the measurement images with large information to perform FPM reconstruction. Simulation and experimental results show that the method produces efficient imaging performance and reduces the required volume of data to more than 65% while ensuring the quality of FPM reconstruction.

Single-shot self-supervised object detection in microscopy

Object detection is a fundamental task in digital microscopy, where machine learning has made great strides in overcoming the limitations of classical approaches. The training of state-of-the-art machine-learning methods almost universally relies on vast amounts of labeled experimental data or the ability to numerically simulate realistic datasets. However, experimental data are often challenging to label and cannot be easily reproduced numerically. Here, we propose a deep-learning method, named LodeSTAR (Localization and detection from Symmetries, Translations And Rotations), that learns to detect microscopic objects with sub-pixel accuracy from a single unlabeled experimental image by exploiting the inherent roto-translational symmetries of this task. We demonstrate that LodeSTAR outperforms traditional methods in terms of accuracy, also when analyzing challenging experimental data containing densely packed cells or noisy backgrounds. Furthermore, by exploiting additional symmetries we show that LodeSTAR can measure other properties, e.g., vertical position and polarizability in holographic microscopy.

Biomass measurements of single neurites in vitro using optical wavefront microscopy

Quantitative phase microscopies (QPMs) enable label-free, non-invasive observation of living cells in culture, for arbitrarily long periods of time. One of the main benefits of QPMs compared with fluorescence microscopy is the possibility to measure the dry mass of individual cells or organelles. While QPM dry mass measurements on neural cells have been reported this last decade, dry mass measurements on their neurites has been very little addressed. Because neurites are tenuous objects, they are difficult to precisely characterize and segment using most QPMs. In this article, we use cross-grating wavefront microscopy (CGM), a high-resolution wavefront imaging technique, to measure the dry mass of individual neurites of primary neurons in vitro. CGM is based on the simple association of a cross-grating positioned in front of a camera, and can detect wavefront distortions smaller than a hydrogen atom (∼0.1 nm). In this article, an algorithm for dry-mass measurement of neurites from CGM images is detailed and provided. With objects as small as neurites, we highlight the importance of dealing with the diffraction rings for proper image segmentation and accurate biomass measurements. The high precision of the measurements we obtain using CGM and this semi-manual algorithm enabled us to detect periodic oscillations of neurites never observed before, demonstrating the sufficient degree of accuracy of CGM to capture the cell dynamics at the single neurite level, with a typical precision of 2%, i.e., 0.08 pg in most cases, down to a few fg for the smallest objects.

Stain-free identification of cell nuclei using tomographic phase microscopy in flow cytometry

Quantitative Phase Imaging (QPI) has gained popularity in bioimaging because it can avoid the need for cell staining, which in some cases is difficult or impossible. However, as a result, QPI does not provide labelling of various specific intracellular structures. Here we show a novel computational segmentation method based on statistical inference that makes it possible for QPI techniques to identify the cell nucleus. We demonstrate the approach with refractive index tomograms of stain-free cells reconstructed through the tomographic phase microscopy in flow cytometry mode. In particular, by means of numerical simulations and two cancer cell lines, we demonstrate that the nucleus can be accurately distinguished within the stain-free tomograms. We show that our experimental results are consistent with confocal fluorescence microscopy (FM) data and microfluidic cytofluorimeter outputs. This is a significant step towards extracting specific three-dimensional intracellular structures directly from the phase-contrast data in a typical flow cytometry configuration.

High-throughput determination of dry mass of single bacterial cells by ultrathin membrane resonators

How bacteria are able to maintain their size remains an open question. Techniques that can measure the biomass (dry mass) of single cells with high precision and high-throughput are demanded to elucidate this question. Here, we present a technological approach that combines the transport, guiding and focusing of individual bacteria from solution to the surface of an ultrathin silicon nitride membrane resonator in vacuum. The resonance frequencies of the membrane undergo abrupt variations at the instants where single cells land on the membrane surface. The resonator design displays a quasi-symmetric rectangular shape with an extraordinary capture area of 0.14 mm², while maintaining a high mass resolution of 0.7 fg (1 fg = 10⁻¹⁵g) to precisely resolve the dry mass of single cells. The small rectangularity of the membrane provides unprecedented frequency density of vibration modes that enables to retrieve the mass of individual cells with high accuracy by specially developed inverse problem theory. We apply this approach for profiling the dry mass distribution in Staphylococcus epidermidis and Escherichia coli cells. The technique allows the determination of the dry mass of single bacterial cells with an accuracy of about 1% at an unparalleled throughput of 20 cells/min. Finally, we revisit Koch & Schaechter model developed during 60 s to assess the intrinsic sources of stochasticity that originate cell size heterogeneity in steady-state populations. The results reveal the importance of mass resolution to correctly describe these mechanisms.

A technological approach combines transport, guiding and focusing of individual bacteria from solution to ultrathin membrane resonators for dry mass determination of single cells with accuracy within 1% and throughput of 20 cells/min.

Microplankton life histories revealed by holographic microscopy and deep learning

The marine microbial food web plays a central role in the global carbon cycle. However, our mechanistic understanding of the ocean is biased toward its larger constituents, while rates and biomass fluxes in the microbial food web are mainly inferred from indirect measurements and ensemble averages. Yet, resolution at the level of the individual microplankton is required to advance our understanding of the microbial food web. Here, we demonstrate that, by combining holographic microscopy with deep learning, we can follow microplanktons throughout their lifespan, continuously measuring their three-dimensional position and dry mass. The deep-learning algorithms circumvent the computationally intensive processing of holographic data and allow rapid measurements over extended time periods. This permits us to reliably estimate growth rates, both in terms of dry mass increase and cell divisions, as well as to measure trophic interactions between species such as predation events. The individual resolution provides information about selectivity, individual feeding rates, and handling times for individual microplanktons. The method is particularly useful to detail the rates and routes of organic matter transfer in micro-zooplankton, the most important and least known group of primary consumers in the oceans. Studying individual interactions in idealized small systems provides insights that help us understand microbial food webs and ultimately larger-scale processes. We exemplify this by detailed descriptions of micro-zooplankton feeding events, cell divisions, and long-term monitoring of single cells from division to division.

The uniformity and stability of cellular mass density in mammalian cell culture

Cell dry mass is principally determined by the sum of biosynthesis and degradation. Measurable change in dry mass occurs on a time scale of hours. By contrast, cell volume can change in minutes by altering the osmotic conditions. How changes in dry mass and volume are coupled is a fundamental question in cell size control. If cell volume were proportional to cell dry mass during growth, the cell would always maintain the same cellular mass density, defined as cell dry mass dividing by cell volume. The accuracy and stability against perturbation of this proportionality has never been stringently tested. Normalized Raman Imaging (NoRI), can measure both protein and lipid dry mass density directly. Using this new technique, we have been able to investigate the stability of mass density in response to pharmaceutical and physiological perturbations in three cultured mammalian cell lines. We find a remarkably narrow mass density distribution within cells, that is, significantly tighter than the variability of mass or volume distribution. The measured mass density is independent of the cell cycle. We find that mass density can be modulated directly by extracellular osmolytes or by disruptions of the cytoskeleton. Yet, mass density is surprisingly resistant to pharmacological perturbations of protein synthesis or protein degradation, suggesting there must be some form of feedback control to maintain the homeostasis of mass density when mass is altered. By contrast, physiological perturbations such as starvation or senescence induce significant shifts in mass density. We have begun to shed light on how and why cell mass density remains fixed against some perturbations and yet is sensitive during transitions in physiological state.

Single-shot off-axis digital holographic system with extended field-of-view by using multiplexing method

We propose a new configuration of single-shot off-axis digital holographic system to realize double the camera field-of-view (FOV) of the existing off-axis Mech-Zehnder type holographic setup. The double FOV is obtained by double spatial frequency multiplexing of two different areas of an object beam by inserting a Fresnel bi-prism in it, which divides the object beam into two, both carrying different object information. The image sensor is placed at the plane where these two different FOVs overlap so as to record simultaneously two parts of the wavefront of the object in a single-shot. The multiplexed hologram is carrying two interferometric images corresponding to two different FOVs of the object which are modulated with two different spatial carrier frequencies. The feasibility of the proposed digital holographic system is experimentally demonstrated by imaging two different areas of a resolution test target. The limitation of the proposed system and a method to overcome it, are also discussed. The proposed system is useful in a wide range of applications including microscopy and optical metrology.

Testing anti-cancer drugs with holographic incoherent-light-source quantitative phase imaging

Quantitative Phase Imaging is becoming an important tool in the objective evaluation of cellular responses to experimental treatment. The technique is based on interferometric measurements of the optical thickness of cells in tissue culture reporting on the distribution of dry mass inside the cells. As the measurement of the optical thickness is interferometric, it is not subjected to the Abbe resolution limit, and the use of an incoherent-light source further increases the accuracy practically achieving 0.93nm in optical path difference corresponding to 4.6 femtograms/μm2. Holographic mode reduces the exposure in comparison to phase-shifting or phase-stepping interference microscopy and allows observation of faster dynamics. An attractive application is in the development of novel anti-cancer drugs and there is an important potential for pretesting chemotherapeutic drugs with biopsy material for personalized cancer treatment. The procedure involves the preparation of live cells in tissue culture, seeding them into suitable observation chambers, and time-lapse recording with an adjusted microscope. Subsequent image processing and statistical analysis are essential last steps producing the results, which include rapid measurements of cell growth in terms of dry-mass increase in individual cells, speed of cell motility and other dynamic morphometric parameters.

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.

AFM Microfluidic Cantilevers as Weight Sensors for Live Single Cell Mass Measurements

Reliably measuring small mass changes at the single-cell level is challenging. In this manuscript, we report the use of microfluidic cantilevers in liquid with sub-nanogram scale weight sensing capability for the measurement of cellular mass changes of living single cells. With this instrumentation, we were able to perform fast mass measurements within 3 minutes. We show results of mass measurements of polystyrene and metal beads of various sizes (smallest weight measured at 280 ± 95 pg) and live single-cell mass measurements in a physiologically relevant environment. We also performed finite element analysis to simulate and optimize the structural design and materials of cantilevers. Our simulation results indicate that using polymer materials, such as SU8 and polyimide, could improve the minimal detectable mass by 3-fold compared to conventional silicon cantilevers. The simulations also suggest that smaller dimensions of length, width, and thickness would improve the mass detection capability of microfluidic cantilevers.

Quantitative Phase Imaging: Recent Advances and Expanding Potential in Biomedicine

Quantitative phase imaging (QPI) is a label-free, wide-field microscopy approach with significant opportunities for biomedical applications. QPI uses the natural phase shift of light as it passes through a transparent object, such as a mammalian cell, to quantify biomass distribution and spatial and temporal changes in biomass. Reported in cell studies more than 60 years ago, ongoing advances in QPI hardware and software are leading to numerous applications in biology, with a dramatic expansion in utility over the past two decades. Today, investigations of cell size, morphology, behavior, cellular viscoelasticity, drug efficacy, biomass accumulation and turnover, and transport mechanics are supporting studies of development, physiology, neural activity, cancer, and additional physiological processes and diseases. Here, we review the field of QPI in biology starting with underlying principles, followed by a discussion of technical approaches currently available or being developed, and end with an examination of the breadth of applications in use or under development. We comment on strengths and shortcomings for the deployment of QPI in key biomedical contexts and conclude with emerging challenges and opportunities based on combining QPI with other methodologies that expand the scope and utility of QPI even further.

Developing a Reliable Holographic Flow Cyto-Tomography Apparatus by Optimizing the Experimental Layout and Computational Processing

Digital Holographic Tomography (DHT) has recently been established as a means of retrieving the 3D refractive index mapping of single cells. To make DHT a viable system, it is necessary to develop a reliable and robust holographic apparatus in order that such technology can be utilized outside of specialized optics laboratories and operated in the in-flow modality. In this paper, we propose a quasi-common-path lateral-shearing holographic optical set-up to be used, for the first time, for DHT in a flow-cytometer modality. The proposed solution is able to withstand environmental vibrations that can severely affect the interference process. Furthermore, we have scaled down the system while ensuring that a full 360° rotation of the cells occurs in the field-of-view, in order to retrieve 3D phase-contrast tomograms of single cells flowing along a microfluidic channel. This was achieved by setting the camera sensor at 45° with respect to the microfluidic direction. Additional optimizations were made to the computational elements to ensure the reliable retrieval of 3D refractive index distributions by demonstrating an effective method of tomographic reconstruction, based on high-order total variation. The results were first demonstrated using realistic 3D numerical phantom cells to assess the performance of the proposed high-order total variation method in comparison with the gold-standard algorithm for tomographic reconstructions: namely, filtered back projection. Then, the proposed DHT system and the processing pipeline were experimentally validated for monocytes and mouse embryonic fibroblast NIH-3T3 cells lines. Moreover, the repeatability of these tomographic measurements was also investigated by recording the same cell multiple times and quantifying the ability to provide reliable and comparable tomographic reconstructions, as confirmed by a correlation coefficient greater than 95%. The reported results represent various steps forward in several key aspects of in-flow DHT, thus paving the way for its use in real-world applications.

Multiparametric quantitative phase imaging for real-time, single cell, drug screening in breast cancer

Quantitative phase imaging (QPI) measures the growth rate of individual cells by quantifying changes in mass versus time. Here, we use the breast cancer cell lines MCF-7, BT-474, and MDA-MB-231 to validate QPI as a multiparametric approach for determining response to single-agent therapies. Our method allows for rapid determination of drug sensitivity, cytotoxicity, heterogeneity, and time of response for up to 100,000 individual cells or small clusters in a single experiment. We find that QPI EC50 values are concordant with CellTiter-Glo (CTG), a gold standard metabolic endpoint assay. In addition, we apply multiparametric QPI to characterize cytostatic/cytotoxic and rapid/slow responses and track the emergence of resistant subpopulations. Thus, QPI reveals dynamic changes in response heterogeneity in addition to average population responses, a key advantage over endpoint viability or metabolic assays. Overall, multiparametric QPI reveals a rich picture of cell growth by capturing the dynamics of single-cell responses to candidate therapies.

Optical Cellular Micromotion: A New Paradigm to Measure Tumor Cells Invasion within Gels Mimicking the 3D Tumor Environments

Measuring tumor cell invasiveness through 3D tissues, particularly at the single-cell level, can provide important mechanistic understanding and assist in identifying therapeutic targets of tumor invasion. However, current experimental approaches, including standard in vitro invasion assays, have limited physiological relevance and offer insufficient insight into the vast heterogeneity in tumor cell migration through tissues. To address these issues, here the concept of optical cellular micromotion is reported on, where digital holographic microscopy is used to map the optical nano- to submicrometer thickness fluctuations within single-cells. These fluctuations are driven by the dynamic movement of subcellular structures including the cytoskeleton and inherently associated with the biological processes involved in cell invasion within tissues. It is experimentally demonstrated that the optical cellular micromotion correlates with tumor cells motility and invasiveness both at the population and single-cell levels. In addition, the optical cellular micromotion significantly reduced upon treatment with migrastatic drugs that inhibit tumor cell invasion. These results demonstrate that micromotion measurements can rapidly and non-invasively determine the invasive behavior of single tumor cells within tissues, yielding a new and powerful tool to assess the efficacy of approaches targeting tumor cell invasiveness.

Correlation of biomechanics and cancer cell phenotype by combined Brillouin and Raman spectroscopy of U87-MG glioblastoma cells

The elucidation of biomechanics furthers our understanding of brain tumour biology. Brillouin spectroscopy is a new optical method that addresses viscoelastic properties down to subcellular resolution in a contact-free manner. Moreover, it can be combined with Raman spectroscopy to obtain co-localized biochemical information. Here, we applied co-registered Brillouin and Raman spectroscopy to U87-MG human glioblastoma cells in vitro. Using two-dimensional and three-dimensional cultures, we related biomechanical properties to local biochemical composition at the subcellular level, as well as the cell phenotype. Brillouin and Raman mapping of adherent cells showed that the nucleus and nucleoli are stiffer than the perinuclear region and the cytoplasm. The biomechanics of the cell cytoplasm is affected by culturing conditions, i.e. cells grown as spheroids are stiffer than adherent cells. Inside the spheroids, the presence of lipid droplets as assessed by Raman spectroscopy revealed higher Brillouin shifts that are not related to a local increase in stiffness, but are due to a higher refractive index combined with a lower mass density. This highlights the importance of locally defined biochemical reference data for a correct interpretation of the Brillouin shift of cells and tissues in future studies investigating the biomechanics of brain tumour models by Brillouin spectroscopy.

Nanospermidine in Combination with Nanofenretinide Induces Cell Death in Neuroblastoma Cell Lines

A new strategy to cause cell death in tumors might be the increase of intracellular polyamines at concentrations above their physiological values to trigger the production of oxidation metabolites at levels exceeding cell tolerance. To test this hypothesis, we prepared nanospermidine as a carrier for spermidine penetration into the cells, able to escape the polyamine transport system that strictly regulates intracellular polyamine levels. Nanospermidine was prepared by spermidine encapsulation in nanomicelles and was characterized by size, zeta potential, loading, dimensional stability to dilution, and stability to spermidine leakage. Antitumor activity, ROS production, and cell penetration ability were evaluated in vitro in two neuroblastoma cell lines (NLF and BR6). Nanospermidine was tested as a single agent and in combination with nanofenretinide. Free spermidine was also tested as a comparison. The results indicated that the nanomicelles successfully transported spermidine into the cells inducing cell death in a concentration range (150–200 μM) tenfold lower than that required to provide similar cytotoxicity with free spermidine (1500–2000 μM). Nanofenretinide provided a cytostatic effect in combination with the lowest nanospermidine concentrations evaluated and slightly improved nanospermidine cytotoxicity at the highest concentrations. These data suggest that nanospermidine has the potential to become a new approach in cancer treatment. At the cellular level, in fact, it exploits polyamine catabolism by means of biocompatible doses of spermidine and, in vivo settings, it can exploit the selective accumulation of nanomedicines at the tumor site. Nanofenretinide combination further improves its efficacy. Furthermore, the proven ability of spermidine to activate macrophages and lymphocytes suggests that nanospermidine could inhibit immunosuppression in the tumor environment.

Assessing the growth kinetics and stoichiometry of Escherichia coli at the single-cell level

Microfluidic cultivation and single-cell analysis are inherent parts of modern microbial biotechnology and microbiology. However, implementing biochemical engineering principles based on the kinetics and stoichiometry of growth in microscopic spaces remained unattained. We here present a novel integrated framework that utilizes distinct microfluidic cultivation technologies and single-cell analytics to make the fundamental math of process-oriented biochemical engineering applicable at the single-cell level. A combination of non-invasive optical cell mass determination with sub-pg sensitivity, microfluidic perfusion cultivations for establishing physiological steady-states, and picoliter batch reactors, enabled the quantification of all physiological parameters relevant to approximate a material balance in microfluidic reaction environments. We determined state variables (biomass concentration based on single-cell dry weight and mass density), biomass synthesis rates, and substrate affinities of cells grown in microfluidic environments. Based on this data, we mathematically derived the specific kinetics of substrate uptake and growth stoichiometry in glucose-grown Escherichia coli with single-cell resolution. This framework may initiate microscale material balancing beyond the averaged values obtained from populations as a basis for integrating heterogeneous kinetic and stoichiometric single-cell data into generalized bioprocess models and descriptions.

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.

Quantitative phase velocimetry measures bulk intracellular transport of cell mass during the cell cycle

Transport of mass within cells helps maintain homeostasis and is disrupted by disease and stress. Here, we develop quantitative phase velocimetry (QPV) as a label-free approach to make the invisible flow of mass within cells visible and quantifiable. We benchmark our approach against alternative image registration methods, a theoretical error model, and synthetic data. Our method tracks not just individual labeled particles or molecules, but the entire flow of bulk material through the cell. This enables us to measure diffusivity within distinct cell compartments using a single approach, which we use here for direct comparison of nuclear and cytoplasmic diffusivity. As a label-free method, QPV can be used for long-term tracking to capture dynamics through the cell cycle.

Effects of Regioisomerism on the Antiproliferative Activity of Hydroxystearic Acids on Human Cancer Cell Lines

A series of regioisomers of the hydroxystearic acid (HSA) was prepared, and the effect of the position of the hydroxyl group along the chain on a panel of human cancer cell lines was investigated. Among the various regioisomers, those carrying the hydroxyl at positions 5, 7, and 9 had growth inhibitor activity against various human tumor cell lines, including CaCo-2, HT29, HeLa, MCF7, PC3, and NLF cells. 10-HSA and 11-HSA showed a very weak effect. 8-HSA did not show inhibitory activity in all cell lines. The biological role of 7-HSA and 9-HSA is widely recognized, while little is known about the effects of 5-HSA. Therefore, the biological effects of 5-HSA in HeLa, HT29, MCF7, and NLF cell lines were investigated using the Livecyte's ptychography technology, which allows correlating changes in proliferation, motility, and morphology as a function of treatment at the same time. 5-HSA not only reduces cell proliferation but also induces changes in cell displacement, directionality, and speed. It is important to characterize the biological effects of 5-HSA, this molecule being an important component of fatty acyl esters of hydroxy fatty acids (FAHFA), a class of endogenous mammalian lipids with noticeable anti-diabetic and anti-inflammatory effects.

Multimodal biomicroscopic system for the characterization of cells with high spatial phase sensitivity and sub-pixel accuracy

Multimodal analysis is highly advantageous for various biomedical applications including cancer and brain studies. Simultaneous measurement of quantitative phase with sub-pixel accuracy and fluorescence image is difficult to achieve in single measurement. Conventionally, off-axis interferograms are analyzed using the Fourier-transform method which limits the accuracy of the phase maps by pixel size, and usually the location of the carrier peak is in sub-pixel. We report a multimodal microscopic system consisting of high-resolution (HR) quantitative phase interferometer to retrieve sub-pixel accuracy in phase imaging and an oblique-illumination-based fluorescence imaging system which decouples the excited light from emitted signal light to avoid saturation of the camera, both integrated into a single unit. Here, highly resolved phase maps are obtained using a two-step process. First, using a speckle-free illumination which offers high spatial phase sensitivity. Second, using a hamming window for accurate estimation of original signal frequency information and HR discrete Fourier transform (DFT) which offers sub-pixel accuracy in phase measurements. HR-DFT has computational load of OABβ , where A×B is the size of the interferogram and β is the upsampling factor, making system computationally more robust and efficient compared to zero-padded FFT. The experiment is conducted on MG63 osteosarcoma and human mesenchymal stem cells (hMSCs) and their quantitative parameters are extracted with significantly improved accuracy. The average phase for MG63 cells and hMSCs, for nucleus is obtained to be 8.02 rad ± 0.80 rad and 4.29 rad ± 0.43 rad, respectively, and for cytoplasm is obtained to be 2.63 rad ± 0.96 rad and 1.73 rad ± 0.57 rad, respectively.

Digital Holographic Microscopy for Label-Free Detection of Leukocyte Alternations Associated with Perioperative Inflammation after Cardiac Surgery

In a prospective observational pilot study on patients undergoing elective cardiac surgery with cardiopulmonary bypass, we evaluated label-free quantitative phase imaging (QPI) with digital holographic microscopy (DHM) to describe perioperative inflammation by changes in biophysical cell properties of lymphocytes and monocytes. Blood samples from 25 patients were investigated prior to cardiac surgery and postoperatively at day 1, 3 and 6. Biophysical and morphological cell parameters accessible with DHM, such as cell volume, refractive index, dry mass, and cell shape related form factor, were acquired and compared to common flow cytometric blood cell markers of inflammation and selected routine laboratory parameters. In all examined patients, cardiac surgery induced an acute inflammatory response as indicated by changes in routine laboratory parameters and flow cytometric cell markers. DHM results were associated with routine laboratory and flow cytometric data and correlated with complications in the postoperative course. In a subgroup analysis, patients were classified according to the inflammation related C-reactive protein (CRP) level, treatment with epinephrine and the occurrence of postoperative complications. Patients with regular courses, without epinephrine treatment and with low CRP values showed a postoperative lymphocyte volume increase. In contrast, the group of patients with increased CRP levels indicated an even further enlarged lymphocyte volume, while for the groups of epinephrine treated patients and patients with complicative courses, no postoperative lymphocyte volume changes were detected. In summary, the study demonstrates the capability of DHM to describe biophysical cell parameters of perioperative lymphocytes and monocytes changes in cardiac surgery patients. The pattern of correlations between biophysical DHM data and laboratory parameters, flow cytometric cell markers, and the postoperative course exemplify DHM as a promising diagnostic tool for a characterization of inflammatory processes and course of disease.

Speeding up reconstruction of 3D tomograms in holographic flow cytometry via deep learning

Tomographic flow cytometry by digital holography is an emerging imaging modality capable of collecting multiple views of moving and rotating cells with the aim of recovering their refractive index distribution in 3D. Although this modality allows us to access high-resolution imaging with high-throughput, the huge amount of time-lapse holographic images to be processed (hundreds of digital holograms per cell) constitutes the actual bottleneck. This prevents the system from being suitable for lab-on-a-chip platforms in real-world applications, where fast analysis of measured data is mandatory. Here we demonstrate a significant speeding-up reconstruction of phase-contrast tomograms by introducing in the processing pipeline a multi-scale fully-convolutional context aggregation network. Although it was originally developed in the context of semantic image analysis, we demonstrate for the first time that it can be successfully adapted to a holographic lab-on-chip platform for achieving 3D tomograms through a faster computational process. We trained the network with input-output image pairs to reproduce the end-to-end holographic reconstruction process, i.e. recovering quantitative phase maps (QPMs) of single cells from their digital holograms. Then, the sequence of QPMs of the same rotating cell is used to perform the tomographic reconstruction. The proposed approach significantly reduces the computational time for retrieving tomograms, thus making them available in a few seconds instead of tens of minutes, while essentially preserving the high-content information of tomographic data. Moreover, we have accomplished a compact deep convolutional neural network parameterization that can fit into on-chip SRAM and a small memory footprint, thus demonstrating its possible exploitation to provide onboard computations for lab-on-chip devices with low processing hardware resources.

Viscoelasticity, Like Forces, Plays a Role in Mechanotransduction

Viscoelasticity and its alteration in time and space has turned out to act as a key element in fundamental biological processes in living systems, such as morphogenesis and motility. Based on experimental and theoretical findings it can be proposed that viscoelasticity of cells, spheroids and tissues seems to be a collective characteristic that demands macromolecular, intracellular component and intercellular interactions. A major challenge is to couple the alterations in the macroscopic structural or material characteristics of cells, spheroids and tissues, such as cell and tissue phase transitions, to the microscopic interferences of their elements. Therefore, the biophysical technologies need to be improved, advanced and connected to classical biological assays. In this review, the viscoelastic nature of cytoskeletal, extracellular and cellular networks is presented and discussed. Viscoelasticity is conceptualized as a major contributor to cell migration and invasion and it is discussed whether it can serve as a biomarker for the cells' migratory capacity in several biological contexts. It can be hypothesized that the statistical mechanics of intra- and extracellular networks may be applied in the future as a powerful tool to explore quantitatively the biomechanical foundation of viscoelasticity over a broad range of time and length scales. Finally, the importance of the cellular viscoelasticity is illustrated in identifying and characterizing multiple disorders, such as cancer, tissue injuries, acute or chronic inflammations or fibrotic diseases.

Pump-free microfluidic magnetic levitation approach for density-based cell characterization

Magnetic levitation (MagLev) provides a simple but promising method for density-based analysis and detection down to the individual cell level. However, each existing MagLev configuration for the single-cell density measurement, mainly consisting of a capillary (∼50 mm) placed between two magnets, yields a fairly low sample utilization because of no knowledge about the sample cells in the regions other than the limited microscope vision. Moreover, the quantitative analysis may be affected due to the unclearly defined measurement area, which is specifically associated with the uneven magnetization of magnets, cell size, degree of aggregation. In this work, we explore a pump-free microfluidic magnetic levitation approach for density-based cell characterization, enabling sensitive and effective cellular density measurement on small sample volumes. The microfluidic MagLev comprises a pump-free microfluidic chip placed between two ring magnets with like poles facing. With no external pumps, connectors or control facility, much smaller amounts of fluids (∼4 μL) could be driven automatically in the entire microchannel in 16 s. Based on the pump-free mechanism, unique density signatures of cells from different lineages (ARPE-19, HCT116, HeLa, HT1080, Huh7) are characterized by monitoring the levitation profiles. Furthermore, variation in density of A549 lung cancer cells subjected to a drug treatment are observed in our platform, allowing evaluation of the efficacy of the drug treatment at the individual cell level. Thereby, the proposed pump-free microfluidic MagLev platform, a low-cost, fully automatic and portable design for label-free density-based cell characterization, provides a universal detection tool that operates efficiently within small-volume environments.