Label-free Cell Research Articles

Particle Self-Aligning, Focusing, and Electric Impedance Microcytometer Device for Label-Free Single Cell Morphology Discrimination and Yeast Budding Analysis.

Microfluidic electric impedance flow cytometry (IFC) devices have been applied in single cell analysis, such as cell counting, volume discrimination, cell viability, etc. A cell's shape provides specific information about cellular physiological and pathological conditions, especially in microorganisms such as yeast. In this study, the particle orientation focusing was theoretically analyzed and realized by hydrodynamics. The pulse width (passing time for the particles) of the conductance signal was used to discriminate particle shapes. Spherical and rod-shaped particles with similar volumes/lengths were differentiated by the IFC device, using the impedance pulse parameters of the events. Then, typical late-budding, early budding, and unbudded yeast cells were distinguished by the width, amplitude, and ratio of width to amplitude (R) of the impedance pulse. The pulse amplitude and the R combination gate for identifying the late-budding yeast was estimated through the statistic results. Using the gate, the late-budding rates under different conditions were calculated. Late-budding rates obtained using our method showed a high correlation (R2 = 0.83) with the manual cell counting result and represented the budding status of yeast cells under different conditions proficiently. Thus, the late-budding rate calculated using the above method can be used as a qualitative parameter to assess the reproductive performance of yeast and whether a yeast culturing environment is optimal. This IFC device and cell shape discrimination method is very simple and could be applied in the fermentation industry and other microorganisms' discrimination as a rapid analysis technique in the future.

Fluorescence-Activated Cell Sorting Is More Potent to Fish Intervertebral Disk Progenitor Cells Than Magnetic and Beads-Based Methods.

Low back pain related to intervertebral disk (IVD) degeneration has a major socioeconomic impact on our aging society. Therefore, stem cell therapy to activate self-repair of the IVD remains an exciting treatment strategy. In this respect, tissue-specific progenitors may play a crucial role in IVD regeneration, as these cells are perfectly adapted to this niche. Such a rare progenitor cell population residing in the nucleus pulposus (NP) (NP progenitor cells [NPPCs]) was found positive for the angiopoietin-1 receptor (Tie2+), and was demonstrated to possess self-renewal capacity and in vitro multipotency. Here, we compared three sorting protocols; that is, fluorescence-activated cell sorting (FACS), magnetic-activated cell sorting (MACS), and a mesh-based label-free cell sorting system (pluriSelect), with respect to cell yield, potential to form colonies (colony-forming units), and in vitro functional differentiation assays for tripotency. The aim of this study was to demonstrate the efficiency of three widespread cell sorting methods for picking rare cells (<5%) and how these isolated cells then behave in downstream functional differentiation in adipogenesis, osteogenesis, and chondrogenesis. The cell yields among the isolation methods differed widely, with FACS presenting the highest yield (5.0% ± 4.0%), followed by MACS (1.6% ± 2.9%) and pluriSelect (1.1% ± 1.0%). The number of colonies formed was not significantly different between Tie2+ and Tie2- NPPCs. Only FACS was able to separate into two functionally different populations that showed trilineage multipotency, while MACS and pluriSelect failed to maintain a clear separation between Tie2+ and Tie2- populations in differentiation assays. To conclude, the isolation of NPPCs was possible with all three sorting methods, while FACS was the preferred technique for separation of functional Tie2+ cells. Impact Statement Tissue-specific progenitor cells such as nucleus pulposus progenitor cells of the IVD could become an ultimate cell source for tissue engineering strategies as these cells are presumably best adapted to the tissue's microenvironment. Fluorescence-activated cell sorting seemed to outcompete magnetic-activated cell sorting and pluriSelect concerning selecting a rare cell population from IVD tissue as could be demonstrated by improved cell yield and functional differentiation assays.

Multiplex coherent anti-Stokes Raman scattering highlights state of chromatin condensation in CH region

Coherent Raman microscopy has become a powerful tool in label-free, non-destructive and fast cell imaging. Here we apply high spectral resolution multiplex coherent anti-Stokes Raman scattering (MCARS) microspectroscopy in the high wavenumber region to the study of the cell cycle. We show that heterochromatin - the condensed state of chromatin - can be visualised by means of the vibrational signature of proteins taking part in its condensation. Thus, we are able to identify chromosomes and their movement during mitosis, as well as structures like nucleoli and nuclear border in interphase. Furthermore, the specific organization of the endoplasmic reticulum during mitosis is highlighted. Finally, we stress that MCARS can reveal the biochemical impact of the fixative method at the cellular level. Beyond the study of the cell cycle, this work introduces a label-free imaging approach that enables the visualization of cellular processes where chromatin undergoes rearrangements.

Design and fabrication of AlN-on-Si chirped surface acoustic wave resonators for label-free cell detection

Chirped surface acoustic wave (SAW) resonators based on aluminum nitride (AlN) thin films have been designed and fabricated to comprehend the wave propagation characteristics induced by interdigitated transducers (IDTs) deposited on their surfaces. From the simulation results, design and geometry of the metal fingers including their width and pitch play critical roles on the wavelength of the acoustic wave and the mechanical displacement, which subsequently set the device resonant frequency. A single-step metal lift-off process involving photolithography and electron beam metal evaporation has been used to pattern and deposit Cr/Au IDT on AlN-on-Si wafers.

Automated sensing and splitting of stem cell colonies on microraft arrays.

Human induced pluripotent stem cells (hiPSCs) are widely used for disease modeling, tissue engineering, and clinical applications. Although the development of new disease-relevant or customized hiPSC lines is of high importance, current automated hiPSC isolation technologies rely largely on the fluorescent labeling of cells, thus limiting the cell line development from many applications. The objective of this research was to develop a platform for high-throughput hiPSC cytometry and splitting that utilized a label-free cell sensing approach. An image analysis pipeline utilizing background subtraction and standard deviation projections was implemented to detect hiPSC colonies from bright-field microscopy data. The pipeline was incorporated into an automated microscopy system coupling quad microraft cell-isolation arrays, computer-based vision, and algorithms for smart decision making and cell sorting. The pipeline exhibited a hiPSC detection specificity of 98% and a sensitivity of 88%, allowing for the successful tracking of growth for hundreds of microcolonies over 7 days. The automated platform split 170 mother colonies from a microarray within 80 min, and the harvested daughter biopsies were expanded into viable hiPSC colonies suitable for downstream assays, such as polymerase chain reaction (PCR) or continued culture. Transmitted light microscopy offers an alternative, label-free modality for isolating hiPSCs, yet its low contrast and specificity for adherent cells remain a challenge for automation. This novel approach to label-free sensing and microcolony subsampling with the preservation of the mother colony holds the potential for hiPSC colony screening based on a wide range of properties including those measurable only by a cell destructive assay.

Deep Cytometry: Deep learning with Real-time Inference in Cell Sorting and Flow Cytometry

Deep learning has achieved spectacular performance in image and speech recognition and synthesis. It outperforms other machine learning algorithms in problems where large amounts of data are available. In the area of measurement technology, instruments based on the photonic time stretch have established record real-time measurement throughput in spectroscopy, optical coherence tomography, and imaging flow cytometry. These extreme-throughput instruments generate approximately 1 Tbit/s of continuous measurement data and have led to the discovery of rare phenomena in nonlinear and complex systems as well as new types of biomedical instruments. Owing to the abundance of data they generate, time-stretch instruments are a natural fit to deep learning classification. Previously we had shown that high-throughput label-free cell classification with high accuracy can be achieved through a combination of time-stretch microscopy, image processing and feature extraction, followed by deep learning for finding cancer cells in the blood. Such a technology holds promise for early detection of primary cancer or metastasis. Here we describe a new deep learning pipeline, which entirely avoids the slow and computationally costly signal processing and feature extraction steps by a convolutional neural network that directly operates on the measured signals. The improvement in computational efficiency enables low-latency inference and makes this pipeline suitable for cell sorting via deep learning. Our neural network takes less than a few milliseconds to classify the cells, fast enough to provide a decision to a cell sorter for real-time separation of individual target cells. We demonstrate the applicability of our new method in the classification of OT-II white blood cells and SW-480 epithelial cancer cells with more than 95% accuracy in a label-free fashion.

RTCA Monitors the Inhibitory Effect of SWCNTs on the Proliferation of human liver cancer HepG2 cells

To investigate the inhibition of single-walled carbon nanotube (SWCNTs) on the proliferation of human hepatoma HepG2 cells by real-time label-free dynamic cell analysis (RTCA). METHODS: The RTCA system was used to dynamically monitor the effects of different doses (0, 0.5, 1 mg/mL) of SWCNTs on the growth of human hepatoma cells HepG2. RESULTS: SWCNTs at a concentration of 1 mg/mL significantly inhibited cell growth after 48 h of incubation, which was the optimal dose and duration for inhibition of HepG2 cell growth. Conclusion: RTCA system can accurately monitor the growth of HepG2 cells treated with SWCNTs.

Design of Hierarchical Beads for Efficient Label-Free Cell Capture.

Defined hierarchical materials promise cell analysis and call for application-driven design in practical use. The further issue is to develop advanced materials and devices for efficient label-free cell capture with minimum instrumentation. Herein, the design of hierarchical beads is reported for efficient label-free cell capture. Silica nanoparticles (size of ≈15 nm) are coated onto silica spheres (size of ≈200 nm) to achieve nanoscale surface roughness, and then the rough silica spheres are combined with microbeads (≈150-1000 µm in diameter) to assemble hierarchical structures. These hierarchical beads are built via electrostatic interaction, covalent bonding, and nanoparticle adherence. Further, after functionalization by hyaluronic acid (HA), the hierarchical beads display desirable surface hydrophilicity, biocompatibility, and chemical/structural stability. Due to the controlled surface topology and chemistry, HA-functionalized hierarchical beads afford high cell capture efficiency up to 98.7% in a facile label-free manner. This work guides the development of label-free cell capture techniques and contributes to the construction of smart interfaces in bio-systems.

Label-free neuroblastoma cell separation from hematopoietic progenitor cell products using acoustophoresis - towards cell processing of complex biological samples

Processing of complex cell preparations such as blood and peripheral blood progenitor cell (PBPC) transplants using label-free technologies is challenging. Transplant-contaminating neuroblastoma cells (NBCs) can contribute to relapse, and we therefore aimed to provide proof-of-principle evidence that label-free acoustophoretic separation can be applied for diagnostic NBC enrichment and removal (“purging”) from human blood and PBPC products. Neuroblastoma cells spiked into blood and PBPC preparations served as model systems. Acoustophoresis enabled to enrich NBCs from mononuclear peripheral blood cells and PBPC samples with recovery rates of up to 60–97%. When aiming at high purity, NBC purities of up to 90% were realized, however, compromising recovery. Acoustophoretic purging of PBPC products allowed substantial tumour cell depletion of 1.5–2.3 log. PBPC loss under these conditions was considerable (>43%) but could be decreased to less than 10% while still achieving NBC depletion rates of 60–80%. Proliferation of cells was not affected by acoustic separation. These results provide first evidence that NBCs can be acoustically separated from blood and stem cell preparations with high recovery and purity, thus indicating that acoustophoresis is a promising technology for the development of future label-free, non-contact cell processing of complex cell products.

Dynamic Liquid Surface Enhanced Raman Scattering Platform Based on Soft Tubular Microfluidics for Label-Free Cell Detection.

Cell detection is of great significance for biomedical research. Surface enhanced Raman scattering (SERS) has been widely applied to the detection of cells. However, there is still a lack of a general, low-cost, rapid, and sensitive SERS method for cell detection. Herein, a dynamic liquid SERS platform, which combines label-free SERS technique with soft tubular microfluidics for cell detection, is proposed. Compared with common static solid and static liquid measurement, the dynamic liquid SERS platform can present dynamical mixing, precise control of the mixing time, and continuous spectra collection. By characterizing the model molecules, the proposed dynamic liquid SERS platform has successfully demonstrated good stability and repeatability with 1.90% and 4.98% relative standard deviation (RSD), respectively. Three cell lines including one normal breast cell line (MCF-10A) and two breast cancer cell lines (MCF-7 and MDA-MB-231) were investigated in this platform. 270 cell spectra were selected as the training set for the classification of the models based on the K-Nearest Neighbor (K-NN) algorithm. In three independent experiments, three types of cells were identified by a test set containing 180 cell spectra with sensitivities above 83.3% and specificities above 91.6%. The accuracy was 94.1 ± 1.14% among three independent cell identifications. The dynamic liquid SERS platform has shown higher signal intensity, better repeatability, less pretreatment, and obtainment of more spectra with less time consumption. It will be a powerful detection tool in the area of cell research, clinical diagnosis, and food safety.

Toward Label-Free Selective Cell Separation of Different Eukaryotic Cell Lines Using Thermoresponsive Homopolymer Layers.

Ultrathin thermoresponsive poly(di(ethylene glycol) methyl ether methacrylate) (PDEGMA) homopolymer layers are reported as a novel platform for label-free temperature-stimulated cell separation from a coculture of eukaryotic cell lines. Pancreatic tumor cells (PaTu 8988t) and fibroblasts (NIH 3T3) were shown to attach and proliferate on PDEGMA layers with a dry thickness of 5 ± 1 nm at 37 °C. After the cell medium cooled to below the lower critical solution temperature (LCST), PaTu 8988t cells showed a significantly decreased cell area. By contrast, there was no significant change in cell area for NIH 3T3 cells, while they still exhibited lamellipodia and filopodia. PaTu 8988t cells could be detached at 22 °C after flushing gently with the cell medium, while negligible cell detachment was observed for NIH 3T3 cells under identical conditions. This significant difference between PaTu 8988t and NIH 3T3 was due to the different cell adhesion on the culture-medium-derived protein covering the PDEGMA layer. Thus, cell separation from a coculture was achieved successfully by cooling the cell medium to 22 °C, resulting in the desorption of 95 ± 6% of PaTu 8988t cells, while the NIH 3T3 cells remained adherent. Our findings provide an effective, label-free, rapid, and simple approach, exploiting a thermoresponsive homopolymer layer to separate and enrich or isolate cells from mixed cell populations for basic biological research, medical diagnostics, tissue engineering, and cell therapy.

Machine learning-driven label-free cell sorting for CAR-T cell manufacturing

Background & Aim We have developed a label-free high throughput machine learning-driven cell sorter based on cells’ morphological information. The cytometer acquires cell-specific waveform signals containing morphologic information from a defined training set. After a supervised machine learning model is developed from the training set, the cell of interest can be classified and sorted based on the scores obtained by the machine learning model. We investigated that the label-free cell classification and sorting of CAR-T cells to improve manufacturing process. CAR-T therapy has shown innovative therapeutic effects in leukemia treatment. However, many clinical studies have been conducted and the clinical results indicated that quality control for the therapeutic cell production process is always an issue for any cell therapy manufacturing process. Also, an ideal CAR-T cell population or “High-Quality CAR-T” with regard to a T cell subset, phenotype, and CAR construct is under investigation. Detailed analysis of CAR-T cells administered to CLL patients have been conducted and the results revealed the important features of clinically active CAR-T such as its glycolysis status, early memory phenotype or exhaustion low profile. Methods, Results & Conclusion To avoid CAR-T manufacturing failure and/or improve the CAR-T quality, it is necessary to collect enough healthy and functional T cells from the patient by leukapheresis in the manufacturing process. We investigated that our label-free cytometer can discriminate healthy T cells from samples after hemolysis process, wherein CD3 positive T cells and other cells were used as a training set to develop the T cell classifier model. The accuracy of the label-free discrimination of T cells was found to be very high. This label-free classification may allow us to perform the quality control of CAR-T manufacturing without the use of surface markers and at the minimal sample loss.

Isolation and bioactive evaluation of flavonoid glycosides from Lobelia chinensis Lour using two-dimensional liquid chromatography combined with label-free cell phenotypic assays

Flavonoid glycosides are widespread in herbs and often used as medicines and nutraceuticals because of good bioactivities and low toxicities. However, due to their structural complexity and diversity, isolation of flavonoid glycosides and evaluation of their bioactivities are still highly challenging. To solve this problem, a new method for separation and preparation of novel flavonoid glycosides from Lobelia chinensis Lour (L. chinensis) was developed. To avoid the interference of non-flavonoids, a solid phase extraction method was used to selectively enrich the flavonoids from the total extract. Based on hydrophilic and hydrophobic properties of the flavonoid chemical structure consisting of sugar residue and diphenylpropane (C6C3C6) skeleton, a structure-guided method development strategy was employed to design a 2D-HILIC × RPLC system in the first time. After optimization of chromatographic conditions, high selectivity and symmetric peaks of flavonoids were obtained on a zwitterionic Click XIon column and a polar-modified Atlantis T3 column. Based on these two columns, a 2 D-HILIC × RPLC system was constructed and successfully enlarged from the analytical level to the preparative level. In the first dimension, 20 fractions were obtained with good peak shapes at high sample loading. In the second-dimensional preparation, nine compounds were isolated and identified. Seven of them were novel flavonoid glycosides, lobelitin A-G, and two other known compounds were linatin and diosmin, respectively. Their target activities were evaluated via label-free cell phenotypic assays. Four novel flavonoid glycosides lobelitin A-D were found to have agonistic activities at G protein-coupled receptor 35 (GPR35). These results demonstrated that this method was effective to orthogonally separate flavonoids at the preparative level, especially for novel active flavonoid glycosides. The discovery of flavonoid glycosides with novel agonistic activity on GPR35 also sheds light on the mechanisms of action of L. chinensis relevant to its clinical application.

Investigation of a Novel Microfluidic Device for Label-Free Ferrohydrodynamic Cell Separation on a Rotating Disk.

Negative magnetophoresis is a novel and attractive method for continuous microparticle sorting inside a magnetic medium. In this method, diamagnetic particles are sorted based on their sizes using magnetic buoyancy force and without any labeling process. Although this method provides some attractive features, such as low-cost fabrication and ease of operation, there are some obstacles that adversely affect its performance, especially for biological applications. Most types of magnetic media, such as ferrofluids, are not biocompatible, and the time-consuming process of sample preparation can be threatening to the viability of the cells within the sample. Furthermore, in this method, both the target and non-target particles are affected by the magnetic field, and therefore, a high separation efficiency cannot be achieved. In this paper, to isolate the abnormal cells from the other blood cells, a microfluidic device was designed using numerical simulation. This model utilizes negative magnetophoresis on a rotating disk, and to reduce the exposure time of the cells inside the magnetic medium, a micromixer is embedded in the upstream of the separator which rapidly prepares the sample. In this part, diluted blood sample and ferrofluid are mixed together utilizing magnetic force. Afterward, the separator sorts the cells into multiple outlets using magnetic buoyancy force as well as centrifugal force. The numerical procedure employed in this study shows that the proposed model is able to recover ∼100% of the abnormal cells from a particular outlet for binary and ternary separation of the cells with high throughputs. Although this percentage of separation may be lower in reality, the optimization of the proposed design by the numerical method can avoid trial-and-error during costly and time-consuming experiments. Also, the device proposed in this study reduces the exposure time of the cells inside the ferrofluid to just a few seconds, which can improve cell viability.

Biophysical phenotyping of single cells using a differential multiconstriction microfluidic device with self-aligned 3D electrodes

Precise measurement of mechanical and electrical properties of single cells can yield useful information on the physiological and pathological state of cells. In this work, we develop a differential multiconstriction microfluidic device with self-aligned 3D electrodes to simultaneously characterize the deformability, electrical impedance and relaxation index of single cells at a high throughput manner (>430 cell/min). Cells are pressure-driven to flow through a series of sequential microfluidic constrictions, during which deformability, electrical impedance and relaxation index of single cells are extracted simultaneously from impedance spectroscopy measurements. Mechanical and electrical phenotyping of untreated, Cytochalasin B treated and N-Ethylmaleimide treated MCF-7 breast cancer cells demonstrate the ability of our system to distinguish different cell populations purely based on these biophysical properties. In addition, we quantify the classification of different cell types using a back propagation neural network. The trained neural network yields the classification accuracy of 87.8% (electrical impedance), 70.1% (deformability), 42.7% (relaxation index) and 93.3% (combination of electrical impedance, deformability and relaxation index) with high sensitivity (93.3%) and specificity (93.3%) for the test group. Furthermore, we have demonstrated the cell classification of a cell mixture using the presented biophysical phenotyping technique with the trained neural network, which is in quantitative agreement with the flow cytometric analysis using fluorescent labels. The developed concurrent electrical and mechanical phenotyping provide great potential for high-throughput and label-free single cell analysis.

Increasing the throughput of label-free cell assays to study the activation of G-protein-coupled receptors by using a serial agonist exposure protocol.

Label-free, holistic assays, monitoring, for example, the impedance of cells on electrodes, are gaining increasing popularity in the evaluation of G-protein-coupled receptor (GPCR) ligands. It is the strength of these approaches to provide the integrated cellular response non-invasively, highly automated and with a device-dependent time resolution down to several milliseconds. With an increasing number of samples to be studied in parallel, the available time resolution is, however, reduced and the cost for the disposable sensor arrays may become limiting. Inspired by protocols from organ pharmacology, we investigated a simple serial agonist addition assay that circumvents these limitations in impedance-based cellular assays. Using a serial addition of increasing concentrations of a GPCR agonist while continuously monitoring the sample's impedance, we were able to establish a full concentration-response curve for the endogenous agonist histamine on a single layer of U-373 MG cells endogenously expressing the histamine 1 receptor (H1R). This approach is validated with respect to conventional, parallel agonist addition protocols and studies using H1R antagonists such as mepyramine. Applicability of the serial agonist addition assay was shown for other GPCRs known for their signaling via one of the canonical G-protein pathways, Gq, Gi/0 or Gs as well. The serial agonist addition protocol has the potential to further strengthen the output of label-free analysis of GPCR activation.

Electrical measurement and quantification of different cell types by electro chemical impedance spectroscopy

Recently, in the field of regenerative tissue engineering, huge amount of cells are needed for developping new organs and tissues. However, during cell cultivation, cells sometimes show degeneration or change their original characters so that it is needed to separate those cells from original cells. Although fluorescent labeling and magnetic labeling of cells have been used for cell separation, invasive label-free methods are required from the point of view of cell damage. Therefore, our aim is to develop a high-efficiency label-free cell separation system based on the difference in electrical characteristics of cells. In this study, for its first step, an attempt was made to distinguish different type of cells by measuring their electrical properties.

Label-free cell phenotypic study of FFA4 and FFA1 and discovery of novel agonists of FFA4 from natural products.

In this article, pharmacological studies of the free fatty acid receptor (FFA) 4 and FFA1 were conducted in transfected CHO cells (FFA4&FFA1) and HT29 cells with application of a label-free dynamic mass redistribution (DMR) assay. Commercially available compounds including α-linolenic acid (ALA), GW9508, TUG891, GSK137647A, TAK875, MEDICA16, AH7614 and GW1100, were used to validate the assay; real-time tracing of ligand-induced cell responses elucidated pharmacological properties of ligand–receptor interactions. A pool of 140 natural compounds was screened using the CHO-FFA4 cells. Three new FFA4 agonists with novel skeletons were discovered and they were dihydrotanshinone, emodin and acetylshikonin (EC50 values were 32.88, 38.18 and 10.17 μM, respectively). Ligand selectivity was compared between FFA4 and FFA1; dihydrotanshinone and emodin displayed FFA4 selectivity, while acetylshikonin shared FFA1 and FFA4 agonist activities with EC50 values comparable to the endogenous ligand ALA. The three novel FFA4 agonists provide a promising chemical starting point for identification and optimization of drugs used for treating metabolic and inflammatory diseases. Besides, this work will help to explain the mechanism of actions of natural products.

Label-Free Metabolic Classification of Single Cells in Droplets Using the Phasor Approach to Fluorescence Lifetime Imaging Microscopy.

Characterization of single cell metabolism is imperative for understanding subcellular functional and biochemical changes associated with healthy tissue development and the progression of numerous diseases. However, single-cell analysis often requires the use of fluorescent tags and cell lysis followed by genomic profiling to identify the cellular heterogeneity. Identifying individual cells in a noninvasive and label-free manner is crucial for the detection of energy metabolism which will discriminate cell types and most importantly critical for maintaining cell viability for further analysis. Here, we have developed a robust assay using the droplet microfluidic technology together with the phasor approach to fluorescence lifetime imaging microscopy to study cell heterogeneity within and among the leukemia cell lines (K-562 and Jurkat). We have extended these techniques to characterize metabolic differences between proliferating and quiescent cells-a critical step toward label-free single cancer cell dormancy research. The result suggests a droplet-based noninvasive and label-free method to distinguish individual cells based on their metabolic states, which could be used as an upstream phenotypic platform to correlate with genomic statistics. © 2018 International Society for Advancement of Cytometry.

Accessible quantitative phase imaging in confocal microscopy with sinusoidal-phase synthetic optical holography.

We present a technically simple implementation of quantitative phase imaging in confocal microscopy based on synthetic optical holography with sinusoidal-phase reference waves. Using a Mirau interference objective and low-amplitude vertical sample vibration with a piezo-controlled stage, we record synthetic holograms on commercial confocal microscopes (Nikon, model: A1R; Zeiss: model: LSM-880), from which quantitative phase images are reconstructed. We demonstrate our technique by stain-free imaging of cervical (HeLa) and ovarian (ES-2) cancer cells and stem cell (mHAT9a) samples. Our technique has the potential to extend fluorescence imaging applications in confocal microscopy by providing label-free cell finding, monitoring cell morphology, as well as non-perturbing long-time observation of live cells based on quantitative phase contrast.