Study of Phospholipids in Single Cells Using an Integrated Microfluidic Device Combined with Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry

Microfluidics Coupled Mass Spectrometry for Single Cell Multi-Omics

Population-level analysis masks significant heterogeneity between individual cells, making it difficult to accurately reflect the true intricacies of life activities. Microfluidics is a technique that can manipulate individual cells effectively and is commonly coupled with a variety of analytical methods for single-cell analysis. Single-cell omics provides abundant molecular information at the single-cell level, fundamentally revealing differences in cell types and biological states among cell individuals, leading to a deeper understanding of cellular phenotypes and life activities. Herein, this work summarizes the microfluidic chips designed for single-cell isolation, manipulation, trapping, screening, and sorting, including droplet microfluidic chips, microwell arrays, hydrodynamic microfluidic chips, and microchips with microvalves. This work further reviews the studies on single-cell proteomics, metabolomics, lipidomics, and multi-omics based on microfluidics and mass spectrometry. Finally, the challenges and future application of single-cell multi-omics are discussed.

Analytical Techniques for Single-Cell Biochemical Assays of Lipids

Lipids are essential cellular components forming membranes, serving as energy reserves, and acting as chemical messengers. Dysfunction in lipid metabolism and signaling is associated with a wide range of diseases including cancer and autoimmunity. Heterogeneity in cell behavior including lipid signaling is increasingly recognized as a driver of disease and drug resistance. This diversity in cellular responses as well as the roles of lipids in health and disease drive the need to quantify lipids within single cells. Single-cell lipid assays are challenging due to the small size of cells (∼1 pL) and the large numbers of lipid species present at concentrations spanning orders of magnitude. A growing number of methodologies enable assay of large numbers of lipid analytes, perform high-resolution spatial measurements, or permit highly sensitive lipid assays in single cells. Covered in this review are mass spectrometry, Raman imaging, and fluorescence-based assays including microscopy and microseparations.

Microwell array chip-based single-cell analysis

Single-cell profiling is key to uncover the cellular heterogeneity and drives deep understanding of cell fate. In recent years, microfluidics has become an ideal tool for single-cell profiling owing to its benefits of high throughput and automation. Among various microfluidic platforms, microwell has the advantages of simple operation and easy integration with in situ analysis ability, making it an ideal technique for single-cell studies. Herein, recent advances of single-cell analysis based on microwell array chips are summarized. We first introduce the design and preparation of different microwell chips. Then microwell-based cell capture and lysis strategies are discussed. We finally focus on advanced microwell-based analysis of single-cell proteins, nucleic acids, and metabolites. The challenges and opportunities for the development of microwell-based single-cell analysis are also presented.

FACS-assisted single-cell lipidome analysis of phosphatidylcholines and sphingomyelins in cells of different lineages

Recent advances in single-cell genomics and transcriptomics technologies have transformed our understanding of cellular heterogeneity in growth, development, ageing, and disease; however, methods for single-cell lipidomics have comparatively lagged behind in development. We have developed a method for the detection and quantification of a wide range of phosphatidylcholine and sphingomyelin species from single cells that combines fluorescence-assisted cell sorting with automated chip-based nanoESI and shotgun lipidomics. We show herein that our method is capable of quantifying more than 50 different phosphatidylcholine and sphingomyelin species from single cells and can easily distinguish between cells of different lineages or cells treated with exogenous fatty acids. Moreover, our method can detect more subtle differences in the lipidome between cell lines of the same cancer type. Our approach can be run in parallel with other single-cell technologies to deliver near-complete, high-throughput multi-omics data on cells with a similar phenotype and has the capacity to significantly advance our current knowledge on cellular heterogeneity.

MALDI HiPLEX-IHC: multiomic and multimodal imaging of targeted intact proteins in tissues

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is one of the most widely used methods for imaging the spatial distribution of unlabeled small molecules such as metabolites, lipids and drugs in tissues. Recent progress has enabled many improvements including the ability to achieve single cell spatial resolution, 3D-tissue image reconstruction, and the precise identification of different isomeric and isobaric molecules. However, MALDI-MSI of high molecular weight intact proteins in biospecimens has thus far been difficult to achieve. Conventional methods normally require in situ proteolysis and peptide mass fingerprinting, have low spatial resolution, and typically detect only the most highly abundant proteins in an untargeted manner. In addition, MSI-based multiomic and multimodal workflows are needed which can image both small molecules and intact proteins from the same tissue. Such a capability can provide a more comprehensive understanding of the vast complexity of biological systems at the organ, tissue, and cellular levels of both normal and pathological function. A recently introduced top-down spatial imaging approach known as MALDI HiPLEX-IHC (MALDI-IHC for short) provides a basis for achieving this high-information content imaging of tissues and even individual cells. Based on novel photocleavable mass-tags conjugated to antibody probes, high-plex, multimodal and multiomic MALDI-based workflows have been developed to image both small molecules and intact proteins on the same tissue sample. Dual-labeled antibody probes enable multimodal mass spectrometry and fluorescent imaging of targeted intact proteins. A similar approach using the same photocleavable mass-tags can be applied to lectin and other probes. We detail here several examples of MALDI-IHC workflows designed to enable high-plex, multiomic and multimodal imaging of tissues at a spatial resolution as low as 5 µm. This approach is compared to other existing high-plex methods such as imaging mass cytometry, MIBI-TOF, GeoMx and CODEX. Finally, future applications of MALDI-IHC are discussed.

Mass spectrometry imaging to explore molecular heterogeneity in cell culture

Molecular analysis on the single-cell level represents a rapidly growing field in the life sciences. While bulk analysis from a pool of cells provides a general molecular profile, it is blind to heterogeneities between individual cells. This heterogeneity, however, is an inherent property of every cell population. Its analysis is fundamental to understanding the development, function, and role of specific cells of the same genotype that display different phenotypical properties. Single-cell mass spectrometry (MS) aims to provide broad molecular information for a significantly large number of cells to help decipher cellular heterogeneity using statistical analysis. Here, we present a sensitive approach to single-cell MS based on high-resolution MALDI-2-MS imaging in combination with MALDI-compatible staining and use of optical microscopy. Our approach allowed analyzing large amounts of unperturbed cells directly from the growth chamber. Confident coregistration of both modalities enabled a reliable compilation of single-cell mass spectra and a straightforward inclusion of optical as well as mass spectrometric features in the interpretation of data. The resulting multimodal datasets permit the use of various statistical methods like machine learning-driven classification and multivariate analysis based on molecular profile and establish a direct connection of MS data with microscopy information of individual cells. Displaying data in the form of histograms for individual signal intensities helps to investigate heterogeneous expression of specific lipids within the cell culture and to identify subpopulations intuitively. Ultimately, t-MALDI-2-MSI measurements at 2-µm pixel sizes deliver a glimpse of intracellular lipid distributions and reveal molecular profiles for subcellular domains.

Towards high throughput and high information coverage: advanced single-cell mass spectrometric techniques

Mass spectrometry (MS) is attractive for single-cell analysis because of its high sensitivity, rich information, and large dynamic ranges, especially for the single-cell metabolome and proteome analysis. Efforts have been made to deal with the throughput and information coverage problems in typical manual single-cell MS techniques. In this review, advanced techniques to improve the automation and throughput for single-cell sampling and single-cell metabolome and proteome MS detection have been discussed. Furthermore, representative MS-based strategies that can increase the in-depth cellular information coverage and achieve the more comprehensive single-cell multiomics information during high throughput detection have been highlighted, providing an ongoing perspective of the MS performance for the single-cell research.

Single-cell lipidomics with high structural specificity by mass spectrometry

Single-cell analysis is critical to revealing cell-to-cell heterogeneity that would otherwise be lost in ensemble analysis. Detailed lipidome characterization for single cells is still far from mature, especially when considering the highly complex structural diversity of lipids and the limited sample amounts available from a single cell. We report the development of a general strategy enabling single-cell lipidomic analysis with high structural specificity. Cell fixation is applied to retain lipids in the cell during batch treatments prior to single-cell analysis. In addition to tandem mass spectrometry analysis revealing the class and fatty acyl-chain for lipids, batch photochemical derivatization and single-cell droplet treatment are performed to identify the C=C locations and sn-positions of lipids, respectively. Electro-migration combined with droplet-assisted electrospray ionization enables single-cell mass spectrometry analysis with easy operation but high efficiency in sample usage. Four subtypes of human breast cancer cells are correctly classified through quantitative analysis of lipid C=C location or sn-position isomers in ~160 cells. Most importantly, the single-cell deep lipidomics strategy successfully discriminates gefitinib-resistant cells from a population of wild-type human lung cancer cells (HCC827), highlighting its unique capability to promote precision medicine.

Microarray and Mass Spectrometry-Based Methodology for Lipid Profiling of Tissues and Cell Cultures

The recent developments in mass spectrometry have revealed the importance of lipids as biomarkers in the context of different diseases and as indicators of the cell's homeostasis. However, further advances are required to unveil the complex relationships between lipid classes and lipid species with proteins. Here, we present a new methodology that combines microarrays with mass spectrometry to obtain the lipid fingerprint of samples of a different nature in a standardized and fast way, with minimal sample consumption. As a proof of concept, we use the methodology to obtain the lipid fingerprint of 20 rat tissues and to create a lipid library for tissue classification. Then, we combine those results with immunohistochemistry and enzymatic assays to unveil the relationship between some lipid species and two enzymes. Finally, we demonstrate the performance of the methodology to explore changes in lipid composition of the nucleus accumbens from mice subjected to two lipid diets.

Analytical challenges of shotgun lipidomics at different resolution of measurements

The essence of shotgun lipidomics is to maintain consistency of the chemical environment of lipid samples during mass spectrometry acquisition. This strategy is suitable for large-scale quantitative analysis. This strategy also allows sufficient time to collect data to improve the signal-to-noise ratio. The initial approach of shotgun lipidomics was the electrospray ionization (ESI)-based direct infusion mass spectrometry strategy. With development of mass spectrometry for small molecules, shotgun lipidomics methods have been extended to matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) and ambient mass spectrometry, including MS imaging methods. Furthermore, the object of analysis has extended from organ and body fluid levels to tissue and cell levels with technological developments. In this article, we summarize the status and technical challenges of shotgun lipidomics at different resolution of measurements from the mass spectrometry perspective.

Integrating a generalized data analysis workflow with the Single-probe mass spectrometry experiment for single cell metabolomics

We conducted single cell metabolomics studies of live cancer cells through online single cell mass spectrometry (SCMS) experiments combined with a generalized comprehensive data analysis workflow. The SCMS experiments were carried out using the Single-probe device coupled with a mass spectrometer to measure molecular profiles of cells in response to two mitotic inhibitors, taxol and vinblastine, under a series of treatment conditions. SCMS metabolomic data were analyzed using a comprehensive approach, including data pre-treatment, visualization, statistical analysis, machine learning, and pathway enrichment analysis. For comparative studies, traditional liquid chromatography-MS (LC-MS) experiments were conducted using lysates prepared from bulk cell samples. Metabolomic profiles of single cells were visualized through Partial Least Square-Discriminant Analysis (PLS-DA), and the phenotypic biomarkers associated with emerging phenotypes induced by drug treatment were discovered and compared through a series of rigorous statistical analysis. Species of interest were further identified at both the single cell and population levels. In addition, four biological pathways potentially involved in the drug treatment were determined through pathway enrichment analysis. Our work demonstrated the capability of comprehensive pipeline studies of single cell metabolomics. This method can be potentially applied to broader types of SCMS datasets for future pharmaceutical and chemotherapeutic research.

The Ratios of monounsaturated to saturated phosphatidylcholines in lung adenocarcinoma microenvironment analyzed by Liquid Chromatography-Mass spectrometry and imaging Mass spectrometry

Adenocarcinoma is the most common type of lung cancer, and can be classified into various histologic subtypes. However, little is known about the subtype-dependent variations in lipid metabolism processes. We performed dual lipidomic analyses using liquid chromatography–mass spectrometry (LC-MS) and matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) to identify possible biomarkers to distinguish adenocarcinoma specimens from normal lung specimens, and to determine if there are any differences in lipid metabolism among the histologic subtypes (lepidic, acinar, papillary, micropapillary, solid, and mucinous). LC-MS was used to characterize the lipid profiles of lung adenocarcinoma and normal lung tissue, and MALDI-IMS analysis was performed to confirm the results with information on lipid localization within the lung. LC-MS analysis found significant differences in the relative abundances of phosphatidylcholine (PC)(16:0/16:0) (P = 0.0432) and sphingomyelin (SM)(42:2) (P < 0.0001) between adenocarcinoma and normal lung specimens. The ratios of PC(16:0/16:1)/PC(16:0/16:0), PC(16:0/18:1)/PC(16:0/16:0), and PC(16:0/18:1)/PC(16:0/18:0) were significantly higher in adenocarcinoma specimens (P = 0.02221, P = 0.0004, and P = 0.0215, respectively). MALDI-IMS analysis confirmed that these ratios were significantly higher in adenocarcinoma regions of the lung. The ratio of PC(16:0–18:1)/PC(16:0–18:0) was significantly lower in solid subtypes than in other subtypes (P = 0.0028). The monounsaturated/saturated PC ratios may have applications in adenocarcinoma diagnoses and subtyping.

Recent advances in single cell manipulation and biochemical analysis on microfluidics

Single cell analysis has become of great interest with unprecedented capabilities for the systematic investigation of cell-to-cell variation in large populations. Rapid and multi-parametric analysis of intercellular biomolecules at the single-cell level is imperative for the improvement of early disease diagnosis and personalized medicine. However, the small size of cells and the low concentration levels of target biomolecules are critical challenges for single cell analysis. In recent years, microfluidic platforms capable of handling small-volume fluid have been demonstrated to be powerful tools for single cell analysis. In addition, microfluidic techniques allow for precise control of the localized microenvironment, which yield more accurate outcomes. Many different microfluidic techniques have been greatly improved for highly efficient single-cell manipulation and highly sensitive detection over the past few decades. To date, microfluidics-based single cell analysis has become the hot research topic in this field. In this review, we particularly highlight the advances in this field during the past three years in the following three aspects: (1) microfluidic single cell manipulation based on microwells, micropatterns, droplets, traps and flow cytometric methods; (2) detection methods based on fluorescence, mass spectrometry, electrochemical, and polymerase chain reaction-based analysis; (3) applications in the fields of small molecule detection, protein analysis, multidrug resistance analysis, and single cell sequencing with droplet microfluidics. We also discuss future research opportunities by focusing on key performances of throughput, multiparametric target detection and data processing.

Recent advances in single-cell analysis by mass spectrometry

Cells are the most basic structural units that play vital roles in the functioning of living organisms. Analysis of the chemical composition and content of a single cell plays a vital role in ensuring precise investigations of cellular metabolism, and is a crucial aspect of lipidomic and proteomic studies. In addition, structural knowledge provides a better understanding of cell behavior as well as the cellular and subcellular mechanisms. However, single-cell analysis can be very challenging due to the very small size of each cell as well as the large variety and extremely low concentrations of substances found in individual cells. On account of its high sensitivity and selectivity, mass spectrometry holds great promise as an effective technique for single-cell analysis. Numerous mass spectrometric techniques have been developed to elucidate the molecular profiles at the cellular level, including electrospray ionization mass spectrometry (ESI-MS), secondary ion mass spectrometry (SIMS), laser-based mass spectrometry and inductively coupled plasma mass spectrometry (ICP-MS). In this review, the recent advances in single-cell analysis by mass spectrometry are summarized. The strategies of different ionization modes to achieve single-cell analysis are classified and discussed in detail.

Advancing single-cell proteomics and metabolomics with microfluidic technologies

Recent advances in single-cell analysis have unraveled substantial heterogeneity among seemingly identical cells at genomic and transcriptomic levels. These discoveries have urged scientists to develop new tools that are capable of investigating single cells from a broader set of "omics". Proteomics and metabolomics, for instance, are of particular interest as they are closely correlated with a dynamic picture of cellular behaviors and phenotypic identities. The development of such tools requires highly efficient isolation and processing of a large number of individual cells, where techniques such as microfluidics are extremely useful. Here, we review the recent advances in single-cell proteomics and metabolomics, with a focus on microfluidics-based platforms. We highlight a vast array of emerging microfluidic formats for single-cell isolation and manipulation, and how the state-of-the-art analytical tools are coupled with such platforms for proteomic and metabolomic profiling.

Advances in mass spectrometry based single-cell metabolomics

Single cell metabolomics using mass spectrometry can contribute to understanding biological activities in health and disease.

High throughput screening of complex biological samples with mass spectrometry – from bulk measurements to single cell analysis

We review the state of the art in HTS using mass spectrometry with minimal sample preparation from complex biological matrices. We focus on industrial and biotechnological applications.

T-Probe: An Integrated Microscale Device for Online In Situ Single Cell Analysis and Metabolic Profiling Using Mass Spectrometry

The exploration of single cells reveals cell heterogeneity and biological principle of cellular metabolism. Although a number of mass spectrometry (MS) based single cell MS (SCMS) techniques have been dedicatedly developed with high efficiency and sensitivity, limitations still exist. In this work, we introduced a microscale multifunctional device, the T-probe, which integrates cellular contents extraction and immediate ionization, to implement online in situ SCMS analysis at ambient conditions with minimal sample preparation. With high sensitivity and reproducibility, the T-probe was employed for MS analysis of single HeLa cells under control and anticancer drug treatment conditions. Intracellular species and xenobiotic metabolites were detected, and changes of cellular metabolic profiles induced by drug treatment were measured. Combining SCMS experiments with statistical data analyses, including Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) and two-sample t-test, we provided biological insights into cellular metabolic response to drug treatment. Online MS/MS analysis was conducted at single cell level to identify species of interest, including endogenous metabolites and the drug compound. Using the T-probe SCMS technique combined with comprehensive data analyses, we provide an approach to understanding cellular metabolism and evaluate chemotherapies at the single cell level.

Recent advances in the use of microfluidic technologies for single cell analysis

The inherent heterogeneity in cell populations has become of great interest and importance as analytical techniques have improved over the past decades. With the advent of personalized medicine, understanding the impact of this heterogeneity has become an important challenge for the research community. Many different microfluidic approaches with varying levels of throughput and resolution exist to study single cell activity. In this review, we take a broad view of the recent microfluidic developments in single cell analysis based on microwell, microchamber, and droplet platforms. We cover physical, chemical, and molecular biology approaches for cellular and molecular analysis including newly emerging genome-wide analysis.

Profiling and quantifying endogenous molecules in single cells using nano-DESI MS

Nano-DESI MS enables sensitive molecular profiling and quantification of endogenous species in single cells in a higher throughput manner.

Surface-printed microdot array chips coupled with matrix-assisted laser desorption/ionization mass spectrometry for high-throughput single-cell patterning and phospholipid analysis

RATIONALE

Single-cell analysis is very important in several research fields for the heterogeneity of individual cells, which has been well accepted. However, restricted by the size and low content of a single cell, current studies have encountered challenges in high-throughput, high-space resolution and sensitivity, and multicomponent analysis. A methodology of a surface-printed microdot array chip coupled with matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) is presented in this study for high-throughput single-cell patterning and phospholipid analysis.

METHODS

The poly-L-lysine (PLL) used as ink molecule was printed on an oxygen plasma processed indium tin oxide (ITO)-coated glass slide to form a microdot array by micro-contact printing technology. The cell array was then formed on the PLL microarray through electrostatic adsorption force. 9-Aminoacridine (9-AA) matrix was applied on the cell array before it was analyzed by MALDI-TOF MS. MALDI mass spectrometry imaging (MALDI-MSI) was then used for high-throughput, quick measurement, and multicomponent analysis of the cell array.

RESULTS

The single-cell capture efficiency of the cell array formed on the PLL microarray was about 40%. Twelve phospholipids were detected at the single-cell level, and the structures were further confirmed by MS/MS. The MALDI-MSI of selected ions showed a conformity with the cell array. The relative signal intensity data of selected ions were extracted from every pixel in the image within several minutes. The heterogeneity between individual cells was revealed from the relative signal intensity of phospholipids in 1-3 cells.

CONCLUSIONS

Compared to the existing related approaches, high-throughput, quick measurement, and multicomponent single-cell analysis have been realized by our method. Through different ink molecules used for micro-contact printing, the established platform could have the potential to capture and analyze specific cells. Copyright © 2016 John Wiley & Sons, Ltd.

Toward Analysis of Proteins in Single Cells: A Quantitative Approach Employing Isobaric Tags with MALDI Mass Spectrometry Realized with a Microfluidic Platform

Protein identification and quantification in individual cells is essential to understand biological processes such as those involved in cell apoptosis, cancer, biomarker discovery, disease diagnostics, pathology, or therapy. Compared with present single cell genome analysis, probing the protein content of single cells has been hampered by the lack of a protein amplification technique. Here, we report the development of a quantitative mass spectrometric approach combined with microfluidic technology reaching the detection sensitivity of high abundant proteins in single cells. A microfluidic platform with a series of chambers and valves, ensuring a set of defined wells for absolute quantification of targeted proteins, was developed and combined with isotopic labeling strategies employing isobaric tags for relative and absolute quantitation (iTRAQ)-labels. To this aim, we adapted iTRAQ labeling to an on-chip protocol. Simultaneous protein digestion and labeling performed on the microfluidic platform rendered the labeling strategy compatible with all necessary manipulation steps on-chip, including the matrix delivery for MALDI-TOF analysis. We demonstrate this approach with the apoptosis related protein Bcl-2 and quantitatively assess the number of Bcl-2 molecules detected. We anticipate that this approach will eventually allow quantification of protein expression on the single cell level.

Matrix-assisted laser desorption/ionization mass spectrometry imaging of cell cultures for the lipidomic analysis of potential lipid markers in human breast cancer invasion

RATIONALE

Breast cancer is the leading cause of cancer death among women worldwide. Identification of lipid targets that play a role in breast cancer invasion may advance our understanding of the rapid progression of cancer and may lead to the development of new biomarkers for the disease.

METHODS

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) was applied for the lipidomic profiling of two poorly invasive and two highly invasive breast cancer cell lines to identify the differentially accumulated lipids related to the invasive phenotype. The four cell lines were individually grown on indium tin oxide (ITO)-coated glass slides, analyzed as cell cultures. The raster width and matrix for detection were optimized to improve detection sensitivity.

RESULTS

Optimized MSI measurements were performed directly on the cell culture with 9-aminoacridine as matrix, resulting in 215 endogenous compounds detected in positive ion mode and 267 endogenous compounds in negative ion mode in all the four cell lines, representing the largest group of analytes that have been analyzed from cells by a single MSI study. In highly invasive cell lines, 31 lipids including phosphatidylglycerol (PG) and phosphatidic acids were found upregulated and eight lipids including sphingomyelin (SM) downregulated in negative ion mode. The products of de novo fatty acid synthesis incorporated into membrane phospholipids, like oleic-acid-containing PG, may be involved in mitochondrial dysfunction and thus affect the invasion of breast cancer cells. The deficiency of SM may be related to the disruption of apoptosis in highly invasive cancer cells.

CONCLUSIONS

This work uncovered more analytes in cells by MSI than previous reports, providing a better visualization and novel insights to advance our understanding of the relationship between rapid progression of breast cancer and lipid metabolism. The most altered lipids may aid the discovery of diagnostic markers and therapeutic targets of breast cancer.

Multivariate Calibration Approach for Quantitative Determination of Cell-Line Cross Contamination by Intact Cell Mass Spectrometry and Artificial Neural Networks

Cross-contamination of eukaryotic cell lines used in biomedical research represents a highly relevant problem. Analysis of repetitive DNA sequences, such as Short Tandem Repeats (STR), or Simple Sequence Repeats (SSR), is a widely accepted, simple, and commercially available technique to authenticate cell lines. However, it provides only qualitative information that depends on the extent of reference databases for interpretation. In this work, we developed and validated a rapid and routinely applicable method for evaluation of cell culture cross-contamination levels based on mass spectrometric fingerprints of intact mammalian cells coupled with artificial neural networks (ANNs). We used human embryonic stem cells (hESCs) contaminated by either mouse embryonic stem cells (mESCs) or mouse embryonic fibroblasts (MEFs) as a model. We determined the contamination level using a mass spectra database of known calibration mixtures that served as training input for an ANN. The ANN was then capable of correct quantification of the level of contamination of hESCs by mESCs or MEFs. We demonstrate that MS analysis, when linked to proper mathematical instruments, is a tangible tool for unraveling and quantifying heterogeneity in cell cultures. The analysis is applicable in routine scenarios for cell authentication and/or cell phenotyping in general.

Efficient cell capture in an agarose–PDMS hybrid chip for shaped 2D culture under temozolomide stimulation

Arbitrary cell patterning on an agarose microwell array is realized and applied to study glioma cell cultures under temozolomide stimulation.