Method for physiologic phenotype characterization at the single-cell level in non-interacting and interacting cells

Efficient single-cell oxygen consumption rate characterization based on frequency domain fluorescence lifetime imaging microscopy measurement and microfluidic platform

Cell metabolism is critical in regulating normal cell functions to maintain energy homeostasis. In order to monitor cell metabolism, the oxygen consumption rate (OCR) of cells has been characterized as an important factor. In conventional cell analysis, the cells are characterized in bulk due to technical limitations. However, the heterogeneity between the cells cannot be identified. Therefore, single-cell analysis has been proposed to reveal cellular functions and their heterogeneity. In this research, an approach integrating a microfluidic device and widefield frequency domain fluorescence imaging lifetime microscopy (FD-FLIM) for single-cell OCR characterization in an efficient manner is developed. The microfluidic device provides an efficient platform to trap and isolate single cells in microwells with the buffer saline containing an oxygen-sensitive phosphorescent dye. The oxygen tension variation within the microwells can be efficiently estimated by measuring the fluorescence lifetime change using the FD-FLIM, and the OCR values of the single cells can then be calculated. In the experiments, breast cancer (MCF-7) cells are exploited for the OCR measurement. The results demonstrate the functionality of the developed approach and show the heterogeneity among the cells. The developed approach possesses great potential to advance cellular metabolism studies with single-cell resolution.

Oxygen Measurement in Microdevices

Oxygen plays a fundamental role in respiration and metabolism, and quantifying oxygen levels is essential in many environmental, industrial, and research settings. Microdevices facilitate the study of dynamic, oxygen-dependent effects in real time. This review is organized around the key needs for oxygen measurement in microdevices, including integrability into microfabricated systems; sensor dynamic range and sensitivity; spatially resolved measurements to map oxygen over two- or three-dimensional regions of interest; and compatibility with multimodal and multianalyte measurements. After a brief overview of biological readouts of oxygen, followed by oxygen sensor types that have been implemented in microscale devices and sensing mechanisms, this review presents select recent applications in organs-on-chip in vitro models and new sensor capabilities enabling oxygen microscopy, bioprocess manufacturing, and pharmaceutical industries. With the advancement of multiplexed, interconnected sensors and instruments and integration with industry workflows, intelligent microdevice-sensor systems including oxygen sensors will have further impact in environmental science, manufacturing, and medicine.

Single cell transcriptomics: moving towards multi-omics

Single-cell multi-omics analysis helps characterize multiple layers of molecular features at a single-cell scale to provide insights into cellular processes and functions.

Simultaneous Multiparameter Cellular Energy Metabolism Profiling of Small Populations of Cells

Functional and genomic heterogeneity of individual cells are central players in a broad spectrum of normal and disease states. Our knowledge about the role of cellular heterogeneity in tissue and organism function remains limited due to analytical challenges one encounters when performing single cell studies in the context of cell-cell interactions. Information based on bulk samples represents ensemble averages over populations of cells, while data generated from isolated single cells do not account for intercellular interactions. We describe a new technology and demonstrate two important advantages over existing technologies: first, it enables multiparameter energy metabolism profiling of small cell populations (<100 cells)—a sample size that is at least an order of magnitude smaller than other, commercially available technologies; second, it can perform simultaneous real-time measurements of oxygen consumption rate (OCR), extracellular acidification rate (ECAR), and mitochondrial membrane potential (MMP)—a capability not offered by any other commercially available technology. Our results revealed substantial diversity in response kinetics of the three analytes in dysplastic human epithelial esophageal cells and suggest the existence of varying cellular energy metabolism profiles and their kinetics among small populations of cells. The technology represents a powerful analytical tool for multiparameter studies of cellular function.

Perfusion double-channel micropipette probes for oxygen flux mapping with single-cell resolution

Measuring cellular respiration with single-cell spatial resolution is a significant challenge, even with modern tools and techniques. Here, a double-channel micropipette is proposed and investigated as a probe to achieve this goal by sampling fluid near the point of interest. A finite element model (FEM) of this perfusion probe is validated by comparing simulation results with experimental results of hydrodynamically confined fluorescent molecule diffusion. The FEM is then used to investigate the dependence of the oxygen concentration variation and the measurement signal on system parameters, including the pipette's shape, perfusion velocity, position of the oxygen sensors within the pipette, and proximity of the pipette to the substrate. The work demonstrates that the use of perfusion double-barrel micropipette probes enables the detection of oxygen consumption signals with micrometer spatial resolution, while amplifying the signal, as compared to sensors without the perfusion system. In certain flow velocity ranges (depending on pipette geometry and configuration), the perfusion flow increases oxygen concentration gradients formed due to cellular oxygen consumption. An optimal perfusion velocity for respiratory measurements on single cells can be determined for different system parameters (e.g., proximity of the pipette to the substrate). The optimum perfusion velocities calculated in this paper range from 1.9 to 12.5 μm/s. Finally, the FEM model is used to show that the spatial resolution of the probe may be varied by adjusting the pipette tip diameter, which may allow oxygen consumption mapping of cells within tissue, as well as individual cells at subcellular resolution.

A versatile method for dynamically controlled patterning of small populations of epithelial cells on substrates via non-contact piezoelectric inkjet printing

Intercellular interactions play a central role at the tissue and whole organism level modulating key cellular functions in normal and disease states. Studies of cell-cell communications are challenging due to ensemble averaging effects brought about by intrinsic heterogeneity in cellular function which requires such studies to be conducted with small populations of cells. Most of the current methods for producing and studying such small cell populations are complex to implement and require skilled personnel limiting their widespread utility in biomedical research labs. We present a simple and rapid method to produce small populations with varying size of epithelial cells (10-50 cells/population) with high-throughput (~ 1 population/second) on flat surfaces via patterning of extracellular matrix (ECM) proteins and random seeding of cells. We demonstrate that despite inherent limitations of non-contact, drop-on-demand piezoelectric inkjet printing for protein patterning, varying mixtures of ECM proteins can be deposited with high reproducibility and level of control on glass substrates using a set of dynamically adjustable optimized deposition parameters. We demonstrate high consistency for the number of cells per population (~1 cell standard error of mean), the population's size (~0.2 coefficient of variation) and shape, as well as accurate spatial placement of and distance between colonies of a panel of metaplastic and dysplastic esophageal epithelial cells with differing adhesion and motility characteristics. The number of cells per colony, colony size and shape can be varied by dynamically varying the amount of ECM proteins deposited per spatial location and the number of spatial locations on the substrate. The method is applicable to a broad range of biological and biomedical studies including cell-cell communications, cellular microenvironment, migration, and stimulus response.

A platform for high-throughput bioenergy production phenotype characterization in single cells

Driven by an increasing number of studies demonstrating its relevance to a broad variety of disease states, the bioenergy production phenotype has been widely characterized at the bulk sample level. Its cell-to-cell variability, a key player associated with cancer cell survival and recurrence, however, remains poorly understood due to ensemble averaging of the current approaches. We present a technology platform for performing oxygen consumption and extracellular acidification measurements of several hundreds to 1,000 individual cells per assay, while offering simultaneous analysis of cellular communication effects on the energy production phenotype. The platform comprises two major components: a tandem optical sensor for combined oxygen and pH detection, and a microwell device for isolation and analysis of single and few cells in hermetically sealed sub-nanoliter chambers. Our approach revealed subpopulations of cells with aberrant energy production profiles and enables determination of cellular response variability to electron transfer chain inhibitors and ion uncouplers.

Platform for combined analysis of functional and biomolecular phenotypes of the same cell

Functional and molecular cell-to-cell variability is pivotal at the cellular, tissue and whole-organism levels. Yet, the ultimate goal of directly correlating the function of the individual cell with its biomolecular profile remains elusive. We present a platform for integrated analysis of functional and transcriptional phenotypes in the same single cells. We investigated changes in the cellular respiration and gene expression diversity resulting from adaptation to repeated episodes of acute hypoxia in a premalignant progression model. We find differential, progression stage-specific alterations in phenotypic heterogeneity and identify cells with aberrant phenotypes. To our knowledge, this study is the first demonstration of an integrated approach to elucidate how heterogeneity at the transcriptional level manifests in the physiologic profile of individual cells in the context of disease progression.

Transcriptional regulation by normal epithelium of premalignant to malignant progression in Barrett's esophagus

In carcinogenesis, intercellular interactions within and between cell types are critical but remain poorly understood. We present a study on intercellular interactions between normal and premalignant epithelial cells and their functional relevance in the context of premalignant to malignant progression in Barrett's esophagus. Using whole transcriptome profiling we found that in the presence of normal epithelial cells, dysplastic cells but not normal cells, exhibit marked down-regulation of a number of key signaling pathways, including the transforming growth factor beta (TGFβ) and epithelial growth factor (EGF). Functional assays revealed both cell types showed repressed proliferation and significant changes in motility (speed, displacement and directionality) as a result of interactions between the two cell types. Cellular interactions appear to be mediated through both direct cell-cell contact and secreted ligands. The findings of this study are important in that they reveal, for the first time, the effects of cellular communication on gene expression and cellular function between premalignant (dysplastic) epithelial cells and their normal counterparts.

Luminescence materials for pH and oxygen sensing in microbial cells - structures, optical properties, and biological applications

Luminescence including fluorescence and phosphorescence sensors have been demonstrated to be important for studying cell metabolism, and diagnosing diseases and cancer. Various design principles have been employed for the development of sensors in different formats, such as organic molecules, polymers, polymeric hydrogels, and nanoparticles. The integration of the sensing with fluorescence imaging provides valuable tools for biomedical research and applications at not only bulk-cell level but also at single-cell level. In this article, we critically reviewed recent progresses on pH, oxygen, and dual pH and oxygen sensors specifically for their application in microbial cells. In addition, we focused not only on sensor materials with different chemical structures, but also on design and applications of sensors for better understanding cellular metabolism of microbial cells. Finally, we also provided an outlook for future materials design and key challenges in reaching broad applications in microbial cells.

Vorinostat differentially alters 3D nuclear structure of cancer and non-cancerous esophageal cells

The histone deacetylase (HDAC) inhibitor vorinostat has received significant attention in recent years as an 'epigenetic' drug used to treat solid tumors. However, its mechanisms of action are not entirely understood, particularly with regard to its interaction with the aberrations in 3D nuclear structure that accompany neoplastic progression. We investigated the impact of vorinostat on human esophageal epithelial cell lines derived from normal, metaplastic (pre-cancerous), and malignant tissue. Using a combination of novel optical computed tomography (CT)-based quantitative 3D absorption microscopy and conventional confocal fluorescence microscopy, we show that subjecting malignant cells to vorinostat preferentially alters their 3D nuclear architecture relative to non-cancerous cells. Optical CT (cell CT) imaging of fixed single cells showed that drug-treated cancer cells exhibit significant alterations in nuclear morphometry. Confocal microscopy revealed that vorinostat caused changes in the distribution of H3K9ac-marked euchromatin and H3K9me3-marked constitutive heterochromatin. Additionally, 3D immuno-FISH showed that drug-induced expression of the DNA repair gene MGMT was accompanied by spatial relocation toward the center of the nucleus in the nuclei of metaplastic but not in non-neoplastic cells. Our data suggest that vorinostat's differential modulation of 3D nuclear architecture in normal and abnormal cells could play a functional role in its anti-cancer action.

A polymer-based ratiometric intracellular glucose sensor

The glucose metabolism level reflects cell proliferative status. A polymeric glucose ratiometric sensor comprising poly(N-(2-hydroxypropyl)methacrylamide) (PHPMA) and poly[2-(methacryloyloxy)ethyl]trimethylammonium chloride (PMAETMA) was synthesized. Cellular internalization and glucose response of the polymer within HeLa cells were investigated.

A minimally invasive method for retrieving single adherent cells of different types from cultures

The field of single-cell analysis has gained a significant momentum over the last decade. Separation and isolation of individual cells is an indispensable step in almost all currently available single-cell analysis technologies. However, stress levels introduced by such manipulations remain largely unstudied. We present a method for minimally invasive retrieval of selected individual adherent cells of different types from cell cultures. The method is based on a combination of mechanical (shear flow) force and biochemical (trypsin digestion) treatment. We quantified alterations in the transcription levels of stress response genes in individual cells exposed to varying levels of shear flow and trypsinization. We report optimal temperature, RNA preservation reagents, shear force and trypsinization conditions necessary to minimize changes in the stress-related gene expression levels. The method and experimental findings are broadly applicable and can be used by a broad research community working in the field of single cell analysis.

Single-cell heterogeneity in suppression of PC12 differentiation by direct microinjection of a differentiation inhibitor, U0126

Phenotypic and genomic heterogeneity among single cells in a cell population leads to inaccuracy and obscuration in research about mammalian cell differentiation. In order to address the problems regarding bulk analysis on heterogeneous cell populations, it is necessary to accurately regulate and analyze changes in differentiating cells at the single-cell level. To investigate the single-cell changes in PC12 neuronal differentiation that occur when inhibited by U0126, an inhibitor of mitogen-activated protein kinase kinase (MEK), we directly injected the chemical into individual target cells and analyzed the outcomes (neurite outgrowth) at the single-cell level. As a result, we could accurately regulate the quantity of U0126 being introduced into each target cell, which was previously not possible using the common method of simply adding the inhibitor to the culture medium. It was possible to analyze the inhibitive effect of U0126 even when the injected quantity was lower than the lower limit for inhibition when added to culture medium (0.1 μM, identical to 1.2 × 10(8) molecules per cell on dish). In particular, injection of 1.5 × 10(7) molecules into each cell resulted in a 59% decrease of the mean total neurite length. Time-course analysis of neurite outgrowth at the single-cell level using fluorescence staining method showed that the changes in neurite length of differentiating PC12 cells were not homogeneous, but were largely variable across individual target cells.

Single-cell analysis reveals early manifestation of cancerous phenotype in pre-malignant esophageal cells

Cellular heterogeneity plays a pivotal role in a variety of functional processes in vivo including carcinogenesis. However, our knowledge about cell-to-cell diversity and how differences in individual cells manifest in alterations at the population level remains very limited mainly due to the lack of appropriate tools enabling studies at the single-cell level. We present a study on changes in cellular heterogeneity in the context of pre-malignant progression in response to hypoxic stress. Utilizing pre-malignant progression of Barrett's esophagus (BE) as a disease model system we studied molecular mechanisms underlying the progression from metaplastic to dysplastic (pre-cancerous) stage. We used newly developed methods enabling measurements of cell-to-cell differences in copy numbers of mitochondrial DNA, expression levels of a set of mitochondrial and nuclear genes involved in hypoxia response pathways, and mitochondrial membrane potential. In contrast to bulk cell studies reported earlier, our study shows significant differences between metaplastic and dysplastic BE cells in both average values and single-cell parameter distributions of mtDNA copy numbers, mitochondrial function, and mRNA expression levels of studied genes. Based on single-cell data analysis, we propose that mitochondria may be one of the key factors in pre-malignant progression in BE.

Deciphering the single-cell omic: innovative application for translational medicine

Traditional technologies to investigate system biology are limited by the detection of parameters resulting from the averages of large populations of cells, missing cells produced in small numbers, and attempting to uniform the heterogeneity. The advent of proteomics and genomics at a single-cell level has set the basis for an outstanding improvement in analytical technology and data acquisition. It has been well demonstrated that cellular heterogeneity is closely related to numerous stochastic transcriptional events leading to variations in patterns of expression among single genetically identical cells. The new-generation technology of single-cell analysis is able to better characterize a cell's population, identifying and differentiating outlier cells, in order to provide both a single-cell experiment and a corresponding bulk measurement, through the identification, quantification and characterization of all system biology aspects (genomics, transcriptomics, proteomics, metabolomics, degradomics and fluxomics). The movement of omics into single-cell analysis represents a significant and outstanding shift.

Population transcriptomics with single-cell resolution: a new field made possible by microfluidics: a technology for high throughput transcript counting and data-driven definition of cell types

Tissues contain complex populations of cells. Like countries, which are comprised of mixed populations of people, tissues are not homogeneous. Gene expression studies that analyze entire populations of cells from tissues as a mixture are blind to this diversity. Thus, critical information is lost when studying samples rich in specialized but diverse cells such as tumors, iPS colonies, or brain tissue. High throughput methods are needed to address, model and understand the constitutive and stochastic differences between individual cells. Here, we describe microfluidics technologies that utilize a combination of molecular biology and miniaturized labs on chips to study gene expression at the single cell level. We discuss how the characterization of the transcriptome of each cell in a sample will open a new field in gene expression analysis, population transcriptomics, that will change the academic and biomedical analysis of complex samples by defining them as quantified populations of single cells.