Assessing differentiation status of human embryonic stem cells noninvasively using Raman microspectroscopy

Raman spectroscopy analysis of human amniotic fluid cells from fetuses with myelomeningocele

Prenatal surgery for the treatment of spina bifida (myelomeningocele, MMC) significantly enhances the neurological prognosis of the patient. To ensure better protection of the spinal cord by large defects, the application of skin grafts produced with cells gained from the amniotic fluid is presently studied. In order to determine the most appropriate cells for this purpose, we tried to shed light on the extremely complex amniotic fluid cellular composition in healthy and MMC pregnancies. We exploited the potential of micro-Raman spectroscopy to analyse and characterize human amniotic fluid cells in total and putative (cKit/CD117-positive) stem cells of fetuses with MMC in comparison with amniotic fluid cells from healthy individuals, human fetal dermal fibroblasts and adult adipose derived stem cells. We found that (i) the differences between healthy and MMC amniocytes can be attributed to specific spectral regions involving collagen, lipids, sugars, tryptophan, aspartate, glutamate, and carotenoids, (ii) MMC amniotic fluid contains two particular cell populations which are absent or reduced in normal pregnancies, (iii) the cKit-negative healthy amniocyte subpopulation shares molecular features with human fetal fibroblasts. On the one hand we demonstrate a different amniotic fluid cellular composition in healthy and MMC pregnancies, on the other our work confirms micro-Raman spectroscopy to be a valuable tool for discriminating cell populations in unknown mixtures of cells.

Two-Dimensional Clustering of Spectral Changes for the Interpretation of Raman Hyperspectra

Two-dimensional correlation spectroscopy (2D-COS) is a technique that permits the examination of synchronous and asynchronous changes present in hyperspectral data. It produces two-dimensional correlation coefficient maps that represent the mutually correlated changes occurring at all Raman wavenumbers during an implemented perturbation. To focus our analysis on clusters of wavenumbers that tend to change together, we apply a k-means clustering to the wavenumber profiles in the perturbation domain decomposition of the two-dimensional correlation coefficient map. These profiles (or trends) reflect peak intensity changes as a function of the perturbation. We then plot the co-occurrences of cluster members two-dimensionally in a manner analogous to a two-dimensional correlation coefficient map. Because wavenumber profiles are clustered based on their similarity, two-dimensional cluster member spectra reveal which Raman peaks change in a similar manner, rather than how much they are correlated. Furthermore, clustering produces a discrete partitioning of the wavenumbers, thus a two-dimensional cluster member spectrum exhibits a discrete presentation of related Raman peaks as opposed to the more continuous representations in a two-dimensional correlation coefficient map. We demonstrate first the basic principles of the technique with the aid of synthetic data. We then apply it to Raman spectra obtained from a polystyrene perchlorate model system followed by Raman spectra from mammalian cells fixed with different percentages of methanol. Both data sets were designed to produce differential changes in sample components. In both cases, all the peaks pertaining to a given component should then change in a similar manner. We observed that component-based profile clustering did occur for polystyrene and perchlorate in the model system and lipids, nucleic acids, and proteins in the mammalian cell example. This confirmed that the method can translate to "real world" samples. We contrast these results with two-dimensional correlation spectroscopy results. To supplement interpretation, we present the cluster-segmented mean spectrum of the hyperspectral data. Overall, this technique is expected to be a valuable adjunct to two-dimensional correlation spectroscopy to further facilitate hyperspectral data interpretation and analysis.

Toward Gene-Correlated Spatially Resolved Metabolomics with Fingerprint Coherent Raman Imaging

Raman spectroscopy has long been known to provide sufficient information to discriminate distinct cell phenotypes. Underlying this discriminating capability is that Raman spectra provide an overall readout of the metabolic profiles that change with transcriptomic activity. Robustly associating Raman spectral changes with the regulation of specific signaling pathways may be possible, but the spectral signals of interest may be weak and vary somewhat among individuals. Establishing a Raman-to-transcriptome mapping will thus require tightly controlled and easily manipulated biological systems and high-throughput spectral acquisition. We attempt to meet these requirements using broadband coherent anti-Stokes Raman scattering (BCARS) microscopy to spatio-spectrally map the C. elegans hermaphrodite gonad in vivo at subcellular resolution. The C. elegans hermaphrodite gonad is an ideal model system with a sequential, continuous process of highly regulated spatiotemporal cellular events. We demonstrate that the BCARS spatio-spectral signatures correlate with gene expression profiles in the gonad, evincing that BCARS has potential as a spatially resolved omics surrogate.

Saline dry fixation for improved cell composition analysis using Raman spectroscopy

Raman spectroscopy enables the label-free assessment of cellular composition. While live cell analysis is the most accurate approach for cellular Raman spectroscopy, the analysis of fixed cells has proved to be very useful, particularly in collaborative projects where samples need to be serially examined by different laboratories or stored and reanalyzed at a later date. However, many chemicals that are widely used for cell fixation directly affect cellular biomolecules, yielding Raman spectra with missing or altered information. In this article, we compared the suitability of dry-fixation with saline versus chemical fixatives. We compared the Raman spectroscopy of saline dry-fixed cells with the more commonly used formaldehyde and methanol fixation and found that dry-fixed cell spectra preserved more cellular information than either chemical fixative. We also assessed the stability of dry-fixed cells over time and found that they were stable for at least 5 months. Finally, a comparison of dry-fixed and live cell spectra revealed effects due to the hydration state of the cells since they were recovered upon rehydrating dry-fixed samples. Thus, for fixed cell Raman spectroscopy, we recommend dry-fixation with unbuffered saline as a superior method to formaldehyde or methanol fixation.

Non-Invasive Three-Dimensional Cell Analysis in Bioinks by Raman Imaging

3D bioprinting is an emerging biofabrication strategy using bioinks, comprising cells and biocompatible materials, to produce functional tissue models. Despite progress in building increasingly complex objects, biological analyses in printed constructs remain challenging. Especially, methods that allow non-invasive and non-destructive evaluation of embedded cells are largely missing. Here, we implemented Raman imaging for molecular-sensitive investigations on bioprinted objects. Different aspects such as culture formats (2D, 3D-cast, and 3D-printed), cell types (endothelial cells and fibroblasts), and the selection of the biopolymer (alginate, alginate/nanofibrillated cellulose, alginate/gelatin) were considered and evaluated. Raman imaging allowed for marker-independent identification and localization of subcellular components against the surrounding biomaterial background. Furthermore, single-cell analysis of spectral signatures, performed by multivariate analysis, demonstrated discrimination between endothelial cells and fibroblasts and identified cellular features influenced by the bioprinting process. In summary, Raman imaging was successfully established to analyze cells in 3D culture in situ and evaluate them with regard to the localization of different cell types and their molecular phenotype as a valuable tool for quality control of bioprinted objects.

Spectroscopic label-free microscopy of changes in live cell chromatin and biochemical composition in transplantable organoids

Organoids formed from human induced pluripotent stem cells (hiPSCs) could be a limitless source of functional tissue for transplantations in many organs. Unfortunately, fine-tuning differentiation protocols to form large quantities of hiPSC organoids in a controlled, scalable, and reproducible manner is quite difficult and often takes a very long time. Recently, we introduced a new approach of rapid organoid formation from dissociated hiPSCs and endothelial cells using microfabricated cell-repellent microwell arrays. This approach, when combined with real-time label-free Raman spectroscopy of biochemical composition changes and confocal light scattering spectroscopic microscopy of chromatin transition, allows for monitoring live differentiating organoids without the need to sacrifice a sample, substantially shortening the time of protocol fine-tuning. We used this approach to both culture and monitor homogeneous liver organoids that have the main functional features of the human liver and which could be used for cell transplantation liver therapy in humans.

Tracking the Differentiation Status of Human Neural Stem Cells through Label-Free Raman Spectroscopy and Machine Learning-Based Analysis

The ability to noninvasively monitor stem cells' differentiation is important to stem cell studies. Raman spectroscopy is a non-harmful imaging approach that acquires the cellular biochemical signatures. Herein, we report the first use of label-free Raman spectroscopy to characterize the gradual change during the differentiation process of live human neural stem cells (NSCs) in the in vitro cultures. Raman spectra of 600-1800 cm-1 were measured with human NSC cultures from the undifferentiated stage (NSC-predominant) to the highly differentiated one (neuron-predominant) and subsequently analyzed using various mathematical methods. Hierarchical cluster analysis distinguished two cell types (NSCs and neurons) through the spectra. The subsequently derived differentiation rate matched that measured by immunocytochemistry. The key spectral biomarkers were identified by time-dependent trend analysis and principal component analysis. Furthermore, through machine learning-based analysis, a set of eight spectral data points were found to be highly accurate in classifying cell types and predicting the differentiation rate. The predictive accuracy was the highest using the artificial neural network (ANN) and slightly lowered using the logistic regression model and linear discriminant analysis. In conclusion, label-free Raman spectroscopy with the aid of machine learning analysis can provide the noninvasive classification of cell types at the single-cell level and thus accurately track the human NSC differentiation. A set of eight spectral data points combined with the ANN method were found to be the most efficient and accurate. Establishing this non-harmful and efficient strategy will shed light on the in vivo and clinical studies of NSCs.

Vibrational Spectroscopy for In Vitro Monitoring Stem Cell Differentiation

Stem cell technology has attracted considerable attention over recent decades due to its enormous potential in regenerative medicine and disease therapeutics. Studying the underlying mechanisms of stem cell differentiation and tissue generation is critical, and robust methodologies and different technologies are required. Towards establishing improved understanding and optimised triggering and control of differentiation processes, analytical techniques such as flow cytometry, immunohistochemistry, reverse transcription polymerase chain reaction, RNA in situ hybridisation analysis, and fluorescence-activated cell sorting have contributed much. However, progress in the field remains limited because such techniques provide only limited information, as they are only able to address specific, selected aspects of the process, and/or cannot visualise the process at the subcellular level. Additionally, many current analytical techniques involve the disruption of the investigation process (tissue sectioning, immunostaining) and cannot monitor the cellular differentiation process in situ, in real-time. Vibrational spectroscopy, as a label-free, non-invasive and non-destructive analytical technique, appears to be a promising candidate to potentially overcome many of these limitations as it can provide detailed biochemical fingerprint information for analysis of cells, tissues, and body fluids. The technique has been widely used in disease diagnosis and increasingly in stem cell technology. In this work, the efforts regarding the use of vibrational spectroscopy to identify mechanisms of stem cell differentiation at a single cell and tissue level are summarised. Both infrared absorption and Raman spectroscopic investigations are explored, and the relative merits, and future perspectives of the techniques are discussed.

Raman imaging diagnosis of the early stage differentiation of mouse embryonic stem cell (mESC)

Raman microspectroscopy as a non-invasive and label-free technique was applied to diagnose the early stage differentiation of mouse embryonic stem cells. The differentiated and undifferentiated embryonic bodies (EBs) were cultured using handing drop method by the control of Leukemia Inhibitory Factor (LIF). Raman spectra of the periphery cells of differentiated EBs (PrE cells) and those of the interior of undifferentiated EBs (ES cells) were obtained to diagnose the stem cells of different differentiation. It was found from the spectra that the protein content increased as the cells differentiated. Principal component analysis (PCA) was carried out to further analyze the differences between ES cells and PrE cells. The first three principle components contained 98.19% from the total variance. Characteristic bands of ES and PrE cells were chosen to acquire Raman images of two cells according to the results of PCA. In the Raman images, PrE cells had a clear and bright outline in the peripheral areas while ES cells were difficult to identify, this could be a distinct characteristic to discriminate them. The result of the Raman images was consistent with the biological agreement that the differentiated cells were distributed around the periphery.

Applications of Raman spectroscopy in the development of cell therapies: state of the art and future perspectives

This comprehensive review article discusses current and future perspectives of Raman spectroscopy-based analyses of cell therapy processes and products.

Detection and Monitoring of Stem Cell Differentiation Using Nanotechnology

Stem cell differentiation and pluripotency are important stages in the regenerative medicine. The design and fabrication of user-friendly approach to save cost and time as well as monitor this process is crucial. Surface-enhanced Raman spectroscopy (SERS) is a sensitive technique to fabricate smart sensors for biological applications. In this technique, double enhancement effect on SERS signals is induced by utilizing graphene oxide (GO)-encapsulated gold nanoparticles (GNPs). The undifferentiated neural stem cells (NSCs) produced Raman peaks which were 3.5 times higher than those obtained from normal metal structures. The surface decorated using 3D GO-encapsulated GNPs was an effective, cost-saving, and nondestructive tool for distinguishing the differentiation state of NSCs. Moreover, the substrate composed of 3D GO-encapsulated gold nanoparticles was also effective for distinguishing the differentiation state of single NSC by using electrochemical and electrical techniques. Therefore, the recommended technique can be utilized as a powerful nondestructive in situ monitoring tool for the identification of the differentiation potential of various kinds of stem cells.

Raman microspectroscopy: toward a better distinction and profiling of different populations of dental stem cells

AIM

To characterize stem cells originating from different dental tissues (apical papilla [SCAP], dental follicle [DFSC], and pulp [DPSC]) and test the capacity of Raman microspectroscopy to distinguish between the three dental stem cell types.

METHODS

SCAP, DFSC, and DPSC cultures were generated from three immature wisdom teeth originating from three patients. Cell stemness was confirmed by inducing neuro-, osteo-, chondro-, and adipo-differentiaton and by mesenchymal marker expression analysis by flow-cytometry and real-time polymerase chain reaction. Cellular components were then evaluated by Raman microspectroscopy.

RESULTS

We found differences between SCAP, DFSC, and DPSC Raman spectra. The ratio between proteins and nucleic acids (748/770), a parameter for discriminating more differentiated from less differentiated cells, showed significant differences between the three cell types. All cells also displayed a fingerprint region in the 600-700 cm-1 range, and characteristic lipid peaks at positions 1440 cm-1 and 1650 cm-1.

CONCLUSION

Although different dental stem cells exhibited similar Raman spectra, the method enabled us to make subtle distinction between them.

The lipid profile of three Malassezia species assessed by Raman spectroscopy and discriminant analysis

Malassezia yeasts constitute the major eukaryotic cutaneous flora of homoeothermic vertebrates. These lipophilic yeasts are able to cause, trigger, or aggravate common skin diseases under favorable conditions. Species identification and subspecies differentiation is currently based on morphological characteristics, lipid assimilation profile, and molecular tests. Mass spectrometry has been also reported as a reliable, yet costly and labor-intensive, method to classify Malassezia yeasts. Here, we introduce Raman spectroscopy as a new molecular technique able to differentiate three phylogenetically close Malassezia species (M.globosa, M.pachydermatis, and M.sympodialis) by examining their lipid metabolic profile. Using Raman spectroscopy, lipid fingerprints of Malassezia cultures on Leeming-Notman agar, were analyzed by spectral bands assignment and partial least squares discriminant analysis. Our results demonstrate differential utilization of lipid supplements among these three species and the ability of Raman spectroscopy to rapidly and accurately discriminate them by predictive modelling.

Probing primary mesenchymal stem cells differentiation status by micro-Raman spectroscopy

We have employed micro-Raman spectroscopy to get insight into intrinsic biomolecular profile of individual mesenchymal stem cell isolated from periodontal ligament. Furthermore, these cells were stimulated towards adipogenic, chondrogenic, and osteogenic lineages and their status of differentiation was assessed using micro-Raman spectroscopy. In both cases, glass coverslips were used as substrates, due to their wide availability and cost effectiveness. In all sample groups, the same type of behavior was observed, manifested as changes in Raman spectra: the increase of relative intensity of protein/lipid bands and decrease of nucleic acid bands. Comprehensive statistical analysis in the form of principal component analysis was performed, which revealed noticeable grouping of cells with the similar features. Despite the inhomogeneity of primary stem cells and their differentiated lineages, we demonstrated that micro-Raman spectroscopy is sufficient for distinguishing cells' status, which can be valuable for medical and clinical application.

Bone quality assessment of osteogenic cell cultures by Raman microscopy

The use of autologous stem/progenitor cells represents a promising approach to the repair of craniofacial bone defects. The calvarium is recognized as a viable source of stem/progenitor cells that can be transplanted in vitro to form bone. However, it is unclear if bone formed in cell culture is similar in quality to that found in native bone. In this study, the quality of bone mineral formed in osteogenic cell cultures were compared against calvarial bone from postnatal mice. Given the spectroscopic resemblance that exists between cell and collagen spectra, the feasibility of extracting information on cell activity and bone matrix quality were also examined. Stem/progenitor cells isolated from fetal mouse calvaria were cultured onto fused-quartz slides under osteogenic differentiation conditions for 28 days. At specific time intervals, slides were removed and analyzed by Raman microscopy and mineral staining techniques. We show that bone formed in culture at Day 28 resembled calvarial bone from 1-day-old postnatal mice with comparable mineralization, mineral crystallinity, and collagen crosslinks ratios. In contrast, bone formed at Day 28 contained a lower degree of ordered collagen fibrils compared with 1-day-old postnatal bone. Taken together, bone formed in osteogenic cell culture exhibited progressive matrix maturation and mineralization but could not fully replicate the high degree of collagen fibril order found in native bone.

Tracing Hematopoietic Progenitor Cell Neutrophilic Differentiation via Raman Spectroscopy

A major challenge to experimental studies and therapeutic uses of hematopoietic stem cells (HSC) is the limited options for analytical tools that can reliably resolve functional differences in heterogeneous HSC subpopulations at the single cell level. Currently available methods require the use of external labels and/or separate clonogenic and transplantation assays to identify bona fide stem cells, necessitating the harvest of bulk cell populations and long incubation times that obscure how individual HSCs dynamically respond to exogenous and endogenous stimuli. In this study, we employ Raman spectroscopy to noninvasively resolve the dynamics of individual differentiating hematopoietic progenitor cells during the course of neutrophilic differentiation. We collected Raman peaks of individual cells daily over the course of 14-day neutrophilic differentiation. Principal component analysis (PCA) of the Raman peaks revealed spectral differences between individual cells during differentiation that were strongly correlated with changes in the nucleus shape and surface antigen expression, the primary traditional means of monitoring neutrophilic differentiation. Additionally, our results were consistently reproducible in independent rounds of neutrophilic differentiation, as demonstrated by our partial least-squares discriminant analysis (PLS-DA) of the Raman spectral information that predicted the degree of neutrophilic differentiation with high sensitivity and specificity. Our findings highlight the utility and reliability of Raman spectroscopy as a robust molecular imaging tool to monitor the kinetics of HSC differentiation patterns.

Cell type discrimination based on image features of molecular component distribution

Machine learning-based cell classifiers use cell images to automate cell-type discrimination, which is increasingly becoming beneficial in biological studies and biomedical applications. Brightfield or fluorescence images are generally employed as the classifier input variables. We propose to use Raman spectral images and a method to extract features from these spatial patterns and explore the value of this information for cell discrimination. Raman images provide information regarding distribution of chemical compounds of the considered biological entity. Since each spectral wavelength can be used to reconstruct the distribution of a given compound, spectral images provide multiple channels of information, each representing a different pattern, in contrast to brightfield and fluorescence images. Using a dataset of single living cells, we demonstrate that the spatial information can be ranked by a Fisher discriminant score, and that the top-ranked features can accurately classify cell types. This method is compared with the conventional Raman spectral analysis. We also propose to combine the information from whole spectral analyses and selected spatial features and show that this yields higher classification accuracy. This method provides the basis for a novel and systematic analysis of cell-type investigation using Raman spectral imaging, which may benefit several studies and biomedical applications.

Surface-enhanced Raman scattering for rapid hematopoietic stem cell differentiation analysis

Raman-spectroscopy-based methods, such as surface-enhanced Raman spectroscopy, are a well-evolved method to molecular fingerprint cell types. Here we demonstrate that surface-enhanced Raman spectroscopy can enable us to distinguish cell development stages of bone marrow hematopoietic stem cells towards red blood cells through the identification of specific surface-enhanced Raman spectroscopy biomarkers. The approach taken here is to allow cells to take in gold nanoparticles as Raman enhancement platforms for kinetic structural observations presented here through the view of the multidimensional parameter contribution, thereby enabling profiling of bone marrow hematopoietic stem cells acquired from proliferation (stage one), differentiation (stage two), and mature red blood cells (stage three).

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.

Empirical Factors Affecting the Quality of Non-Negative Matrix Factorization of Mammalian Cell Raman Spectra

Mammalian cells contain various macromolecules that can be investigated non-invasively with Raman spectroscopy. The particular mixture of major macromolecules present in a cell being probed are reflected in the measured Raman spectra. Determining macromolecular identities and estimating their concentrations from these mixture Raman spectra can distinguish cell types and otherwise enable biological research. However, the application of canonical multivariate methods, such as principal component analysis (PCA), to perform spectral unmixing yields mathematical solutions that can be difficult to interpret. Non-negative matrix factorization (NNMF) improves the interpretability of unmixed macromolecular components, but can be difficult to apply because ambiguities produced by overlapping Raman bands permit multiple solutions. Furthermore, theoretically sound methods can be difficult to implement in practice. Here we examined the effects of a number of empirical approaches on the quality of NNMF results. These approaches were evaluated on simulated mammalian cell Raman hyperspectra and the results were used to develop an enhanced procedure for implementing NNMF. We demonstrated the utility of this procedure using a Raman hyperspectral data set measured from human islet cells to recover the spectra of insulin and glucagon. This was compared to the relatively inferior PCA of these data.

Label-Free Raman Hyperspectral Imaging of Single Cells Cultured on Polymer Substrates

While Raman hyperspectral imaging has been widely used for label-free mapping of biomolecules in cells, these measurements require the cells to be cultured on weakly Raman scattering substrates. However, many applications in biological sciences and engineering require the cells to be cultured on polymer substrates that often generate large Raman scattering signals. Here, we discuss the theoretical limits of the signal-to-noise ratio in the Raman spectra of cells in the presence of polymer signals and how optical aberrations may affect these measurements. We show that Raman spectra of cells cultured on polymer substrates can be obtained using automatic subtraction of the polymer signals and demonstrate the capabilities of these methods in two important applications: tissue engineering and in vitro toxicology screening of drugs. Apart from their scientific and technological importance, these applications are examples of the two most common measurement configurations: (1) cells cultured on an optically thick polymer substrate measured using an immersion/dipping objective; and (2) cells cultured on a transparent polymer substrate and measured using an inverted optical microscope. In these examples, we show that Raman hyperspectral data sets with sufficient quality can be successfully acquired to map the distribution of common biomolecules in cells, such as nucleic acids, proteins, and lipids, as well as detecting the early stages of apoptosis. We also discuss strategies for further improvements that could expand the application of Raman hyperspectral imaging on polymer substrates even further in biomedical sciences and engineering.

Raman spectroscopy and coherent anti-Stokes Raman scattering imaging: prospective tools for monitoring skeletal cells and skeletal regeneration

The use of skeletal stem cells (SSCs) for cell-based therapies is currently one of the most promising areas for skeletal disease treatment and skeletal tissue repair. The ability for controlled modification of SSCs could provide significant therapeutic potential in regenerative medicine, with the prospect to permanently repopulate a host with stem cells and their progeny. Currently, SSC differentiation into the stromal lineages of bone, fat and cartilage is assessed using different approaches that typically require cell fixation or lysis, which are invasive or even destructive. Raman spectroscopy and coherent anti-Stokes Raman scattering (CARS) microscopy present an exciting alternative for studying biological systems in their natural state, without any perturbation. Here we review the applications of Raman spectroscopy and CARS imaging in stem-cell research, and discuss the potential of these two techniques for evaluating SSCs, skeletal tissues and skeletal regeneration as an exemplar.

Non-Invasive Approaches to Epigenetic-Based Sperm Selection

Since sperm size and form do not necessarily provide information on internal sperm structures, novel sperm markers need to be found in order to conduct assisted reproductive therapies (ART) successfully. Currently, the priority of andrologists is not only to select those sperm able to fertilize the oocyte, but also a high quality of sperm that will guarantee a healthy embryo. Evidence of this shows us the importance of studying sperm intensively on genetic and epigenetic levels, because these could probably be the cause of a percentage of infertility diagnosed as idiopathic. Thus, more attention is being paid to posttranslational modifications as the key for better understanding of the fertilization process and its impact on embryo and offspring. Advances in the discovery of new sperm markers should go hand in hand with finding appropriate techniques for selecting the healthiest sperm, guaranteeing its non-invasiveness. To date, most sperm selection techniques can be harmful to sperm due to centrifugation or staining procedures. Some methods, such as microfluidic techniques, sperm nanopurifications, and Raman spectroscopy, have the potential to make selection gentle to sperm, tracking small abnormalities undetected by methods currently used. The fact that live cells could be analyzed without harmful effects creates the expectation of using them routinely in ART. In this review, we focus on the combination of sperm epigenetic status (modifications) as quality markers, with non-invasive sperm selection methods as novel approaches to improve ART outcomes.

Physico-electrochemical Characterization of Pluripotent Stem Cells during Self-Renewal or Differentiation by a Multi-modal Monitoring System

Monitoring pluripotent stem cell behaviors (self-renewal and differentiation to specific lineages/phenotypes) is critical for a fundamental understanding of stem cell biology and their translational applications. In this study, a multi-modal stem cell monitoring system was developed to quantitatively characterize physico-electrochemical changes of the cells in real time, in relation to cellular activities during self-renewal or lineage-specific differentiation, in a non-destructive, label-free manner. The system was validated by measuring physical (mass) and electrochemical (impedance) changes in human induced pluripotent stem cells undergoing self-renewal, or subjected to mesendodermal or ectodermal differentiation, and correlating them to morphological (size, shape) and biochemical changes (gene/protein expression). An equivalent circuit model was used to further dissect the electrochemical (resistive and capacitive) contributions of distinctive cellular features. Overall, the combination of the physico-electrochemical measurements and electrical circuit modeling collectively offers a means to longitudinally quantify the states of stem cell self-renewal and differentiation.

Osteocalcin Mediates Biomineralization during Osteogenic Maturation in Human Mesenchymal Stromal Cells

There is a growing interest in cell therapies using mesenchymal stromal cells (MSCs) for repairing bone defects. MSCs have the ability to differentiate into osteoprogenitors and osteoblasts as well as to form calcified bone matrix. However, the molecular mechanisms governing mineralization during osteogenic differentiation remain unclear. Non-collagenous proteins in the extracellular matrix are believed to control different aspects of the mineralization. Since osteocalcin is the most abundant non-collagenous bone matrix protein, the purpose of this study is to investigate the roles of osteocalcin in mineral species production during osteogenesis of MSCs. Using Raman spectroscopy, we found that the maturation of mineral species was affected by osteocalcin expression level. After osteocalcin was knocked down, the mineral species maturation was delayed and total hydroxyapatite was lower than the control group. In addition, the expression of osteogenic marker genes, including RUNX2, alkaline phosphatase, type I collagen, and osteonectin, was downregulated during osteogenic differentiation compared to the control group; whereas gene expression of osterix was upregulated after the knockdown. Together, osteocalcin plays an essential role for the maturation of mineral species and modulates osteogenic differentiation of MSCs. The results offer new insights into the enhancement of new bone formation, such as for the treatments of osteoporosis and fracture healing.

Non-label immune cell state prediction using Raman spectroscopy

The acquired immune system, mainly composed of T and B lymphocytes, plays a key role in protecting the host from infection. It is important and technically challenging to identify cell types and their activation status in living and intact immune cells, without staining or killing the cells. Using Raman spectroscopy, we succeeded in discriminating between living T cells and B cells, and visualized the activation status of living T cells without labeling. Although the Raman spectra of T cells and B cells were similar, they could be distinguished by discriminant analysis of the principal components. Raman spectra of activated T cells with anti-CD3 and anti-CD28 antibodies largely differed compared to that of naïve T cells, enabling the prediction of T cell activation status at a single cell level. Our analysis revealed that the spectra of individual T cells gradually change from the pattern of naïve T cells to that of activated T cells during the first 24 h of activation, indicating that changes in Raman spectra reflect slow changes rather than rapid changes in cell state during activation. Our results indicate that the Raman spectrum enables the detection of dynamic changes in individual cell state scattered in a heterogeneous population.

Raman microscopy of bladder cancer cells expressing green fluorescent protein

Gene engineering is a commonly used tool in cellular biology to determine changes in function or expression of downstream targets. However, the impact of genetic modulation on biochemical effects is less frequently evaluated. The aim of this study is to use Raman microscopy to assess the biochemical effects of gene silencing on T24 and UMUC-13 bladder cancer cell lines. Cellular biochemical information related to nucleic acid and lipogenic components was obtained from deconvolved Raman spectra. We show that the green fluorescence protein (GFP), the chromophore that served as a fluorescent reporter for gene silencing, could also be detected by Raman microscopy. Only the gene-silenced UMUC-13 cell lines exhibited low-to-moderate GFP fluorescence as determined by fluorescence imaging and Raman spectroscopic studies. Moreover, we show that gene silencing and cell phenotype had a greater effect on nucleic acid and lipogenic components with minimal interference from GFP expression. Gene silencing was also found to perturb cellular protein secondary structure in which the amount of disorderd protein increased at the expense of more ordered protein. Overall, our study identified the spectral signature for cellular GFP expression and elucidated the effects of gene silencing on cancer cell biochemistry and protein secondary structure.

Label-free live cell imaging by Confocal Raman Microscopy identifies CHO host and producer cell lines

As a possible viable and non-invasive method to identify high producing cells, Confocal Raman Microscopy was shown to be able to differentiate CHO host cell lines and derivative production clones. Cluster analysis of spectra and their derivatives was able to differentiate between different producer cell lines and a host, and also distinguished between an intracellular region of high lipid and protein content that in structure resembles the Endoplasmic Reticulum. This ability to identify the ER may be a major contributor to the identification of high producers. PCA enabled the discrimination even of host cell lines and their subclones with inherently higher production capacity. The method is thus a promising option that may contribute to early, non-invasive identification of high potential candidates during cell line development and possibly could also be used for proof of identity of established production clones.

In vitro biomechanical properties, fluorescence imaging, surface-enhanced Raman spectroscopy, and photothermal therapy evaluation of luminescent functionalized CaMoO4:Eu@Au hybrid nanorods on human lung adenocarcinoma epithelial cells

Highly dispersible Eu3+-doped CaMoO4@Au-nanorod hybrid nanoparticles (HNPs) exhibit optical properties, such as plasmon resonances in the near-infrared region at 790 nm and luminescence at 615 nm, offering multimodal capabilities: fluorescence imaging, surface-enhanced Raman spectroscopy (SERS) detection and photothermal therapy (PTT). HNPs were conjugated with a Raman reporter (4-mercaptobenzoic acid), showing a desired SERS signal (enhancement factor 5.0 × 105). The HNPs have a heat conversion efficiency of 25.6%, and a hyperthermia temperature of 42°C could be achieved by adjusting either concentration of HNPs, or laser power, or irradiation time. HNPs were modified with antibody specific to cancer biomarker epidermal growth factor receptor, then applied to human lung cancer (A549) and mouse hepatocyte cells (AML12), and in vitro PTT effect was studied. In addition, the biomechanical properties of A549 cells were quantified using atomic force microscopy. This study shows the potential applications of these HNPs in fluorescence imaging, SERS detection, and PTT with good photostability and biocompatibility.

Label-free biomarkers of human embryonic stem cell differentiation to hepatocytes

Four different label-free, minimally invasive, live single cell analysis techniques were applied in a quantitative comparison, to characterize embryonic stem cells and the hepatocytes into which they were differentiated. Atomic force microscopy measures the cell's mechanical properties, Raman spectroscopy measures its chemical properties, and dielectrophoresis measures the membrane's capacitance. They were able to assign cell type of individual cells with accuracies of 91% (atomic force microscopy), 95.5% (Raman spectroscopy), and 72% (dielectrophoresis). In addition, stimulated Raman scattering (SRS) microscopy was able to easily identify hepatocytes in images by the presence of lipid droplets. These techniques, used either independently or in combination, offer label-free methods to study individual living cells. Although these minimally invasive biomarkers can be applied to sense phenotypical or environmental changes to cells, these techniques have most potential in human stem cell therapies where the use of traditional biomarkers is best avoided. Destructive assays consume valuable stem cells and do not characterize the cells which go on to be used in therapies; whereas immunolabeling risks altering cell behavior. It was suggested how these four minimally invasive methods could be applied to cell culture, and how they could in future be combined into one microfluidic chip for cell sorting. © 2016 International Society for Advancement of Cytometry.

Multiparameter Analysis of Human Bone Marrow Stromal Cells Identifies Distinct Immunomodulatory and Differentiation-Competent Subtypes

Bone marrow stromal cells (BMSCs, also called bone-marrow-derived mesenchymal stromal cells) provide hematopoietic support and immunoregulation and contain a stem cell fraction capable of skeletogenic differentiation. We used immortalized human BMSC clonal lines for multi-level analysis of functional markers for BMSC subsets. All clones expressed typical BMSC cell-surface antigens; however, clones with trilineage differentiation capacity exhibited enhanced vascular interaction gene sets, whereas non-differentiating clones were uniquely CD317 positive with significantly enriched immunomodulatory transcriptional networks and high IL-7 production. IL-7 lineage tracing and CD317 immunolocalization confirmed the existence of a rare non-differentiating BMSC subtype, distinct from Cxcl12-DsRed(+) perivascular stromal cells in vivo. Colony-forming CD317(+) IL-7(hi) cells, identified at ∼ 1%-3% frequency in heterogeneous human BMSC fractions, were found to have the same biomolecular profile as non-differentiating BMSC clones using Raman spectroscopy. Distinct functional identities can be assigned to BMSC subpopulations, which are likely to have specific roles in immune control, lymphopoiesis, and bone homeostasis.

Methods of Monitoring Cell Fate and Tissue Growth in Three-Dimensional Scaffold-Based Strategies for In Vitro Tissue Engineering

In the field of tissue engineering, there is a need for methods that allow assessing the performance of tissue-engineered constructs noninvasively in vitro and in vivo. To date, histological analysis is the golden standard to retrieve information on tissue growth, cellular distribution, and cell fate on tissue-engineered constructs after in vitro cell culture or on explanted specimens after in vivo applications. Yet, many advances have been made to optimize imaging techniques for monitoring tissue-engineered constructs with a sub-mm or μm resolution. Many imaging modalities have first been developed for clinical applications, in which a high penetration depth has been often more important than lateral resolution. In this study, we have reviewed the current state of the art in several imaging approaches that have shown to be promising in monitoring cell fate and tissue growth upon in vitro culture. Depending on the aimed tissue type and scaffold properties, some imaging methods are more applicable than others. Optical methods are mostly suited for transparent materials such as hydrogels, whereas magnetic resonance-based methods are mostly applied to obtain contrast between hard and soft tissues regardless of their transparency. Overall, this review shows that the field of imaging in scaffold-based tissue engineering is developing at a fast pace and has the potential to overcome the limitations of destructive endpoint analysis.

Raman spectral dynamics of single cells in the early stages of growth factor stimulation

Cell fates change dynamically in response to various extracellular signals, including growth factors that stimulate differentiation and proliferation. The processes underlying cell-fate decisions are complex and often include large cell-to-cell variations, even within a clonal population in the same environment. To understand the origins of these cell-to-cell variations, we must detect the internal dynamics of single cells that reflect their changing chemical milieu. In this study, we used the Raman spectra of single cells to trace their internal dynamics during the early stages of growth factor stimulation. This method allows nondestructive and inclusive time-series analyses of chemical compositions of the same single cells. Applying a Gaussian mixture model to the major principal components of the single-cell Raman spectra, we detected the dynamics of the chemical states in MCF-7 cancer-derived cells in the absence and presence of differentiation and proliferation factors. The dynamics displayed characteristic variations according to the functions of the growth factors. In the differentiation pathway, the chemical composition changed directionally between multiple states, including both reversible and irreversible state transitions. In contrast, in the proliferation pathway, the chemical composition was homogenized into a single state. The differentiation factor also stimulated fluctuations in the chemical composition, whereas the proliferation factor did not.

Identifying States along the Hematopoietic Stem Cell Differentiation Hierarchy with Single Cell Specificity via Raman Spectroscopy

A major challenge for expanding specific types of hematopoietic cells ex vivo for the treatment of blood cell pathologies is identifying the combinations of cellular and matrix cues that direct hematopoietic stem cells (HSC) to self-renew or differentiate into cell populations ex vivo. Microscale screening platforms enable minimizing the number of rare HSCs required to screen the effects of numerous cues on HSC fate decisions. These platforms create a strong demand for label-free methods that accurately identify the fate decisions of individual hematopoietic cells at specific locations on the platform. We demonstrate the capacity to identify discrete cells along the HSC differentiation hierarchy via multivariate analysis of Raman spectra. Notably, cell state identification is accurate for individual cells and independent of the biophysical properties of the functionalized polyacrylamide gels upon which these cells are cultured. We report partial least-squares discriminant analysis (PLS-DA) models of single cell Raman spectra enable identifying four dissimilar hematopoietic cell populations across the HSC lineage specification. Successful discrimination was obtained for a population enriched for long-term repopulating HSCs (LT-HSCs) versus their more differentiated progeny, including closely related short-term repopulating HSCs (ST-HSCs) and fully differentiated lymphoid (B cells) and myeloid (granulocytes) cells. The lineage-specific differentiation states of cells from these four subpopulations were accurately identified independent of the stiffness of the underlying biomaterial substrate, indicating subtle spectral variations that discriminated these populations were not masked by features from the culture substrate. This approach enables identifying the lineage-specific differentiation stages of hematopoietic cells on biomaterial substrates of differing composition and may facilitate correlating hematopoietic cell fate decisions with the extrinsic cues that elicited them.

Aseptic Raman spectroscopy can detect changes associated with the culture of human dental pulp stromal cells in osteoinductive culture

There is an unmet need for the non-invasive characterisation of stem cells to facilitate the translation of cell-based therapies. Raman spectroscopy has proven utility in stem cell characterisation but as yet no method has been reported capable of taking repeated Raman measurements of living cells aseptically over time. The aim of this study was to determine if Raman spectroscopy could be used to monitor changes in a well characterised cell population (human dental pulp stromal cells (DPSCs)) by taking repeated Raman measurements from the same cell populations in osteoinductive culture over time and under aseptic conditions. DPSCs were isolated from extracted premolar teeth from 3 consenting donors. Following in vitro expansion, DPSCs were maintained for 28 days in osteo-inductive medium. Raman spectra were acquired from the cells at days 0, 3, 7, 10, 14 and 28. Principal component analysis (PCA) was carried out to assess if there was any temporal spectral variation. At day 28, osteoinduction was confirmed using alizarin red staining and qRT-PCR for alkaline phosphatase and osteocalcin. Alizarin red staining was positive in all samples at day 28 and significant increases in alkaline phosphatase (p < 0.001) and osteocalcin (p < 0.05) gene expression were also observed compared with day 0. PCA of the Raman data demonstrated trends in PC1 from days 0-10, influenced by protein associated features and PC2 from days 10-28, influenced by DNA/RNA associated features. We conclude that spectroscopy can be used to monitor changes in Raman signature with time associated with the osteoinduction of DPSCs using repeated measurements via an aseptic methodology.

Label-free assessment of replicative senescence in mesenchymal stem cells by Raman microspectroscopy

Here, Raman microspectroscopy was employed to assess replicative senescence of mesenchymal stem cells (MSC). A regular spectral change related to the cell senescence was found in the ratio of two peaks at 1157 cm(-1) and 1174 cm(-1), which are assigned to C-C, C-N stretching vibrations in proteins and C-H bending vibrations in tyrosine and phenylalanine, respectively. With the cell aging, the ratio I1157 / I1174 exhibited a monotonic decline and showed small standard deviations, so that it can statistically distinguish between cells having slight changes in terms of aging. We propose that I1157 / I1174 can act as a characteristic spectral signature for label-free assessment of MSC senescence.

Label-free and non-invasive monitoring of porcine trophoblast derived cells: differentiation in serum and serum-free media

Traditional approaches to characterize stem cell differentiation are time-consuming, lengthy and invasive. Here, Raman microspectroscopy (RM) and atomic force microscopy (AFM) - both considered as non-invasive techniques - are applied to detect the biochemical and biophysical properties of trophoblast derived stem-like cells incubated up to 10 days under conditions designed to induce differentiation. Significant biochemical and biophysical differences between control cells and differentiated cells were observed. Quantitative real time PCR was also applied to analyze gene expression. The relationship between cell differentiation and associated cellular biochemical and biomechanical changes were discussed. Monitoring trophoblast cells differentiation.

Time-lapse Raman imaging of osteoblast differentiation

Osteoblastic mineralization occurs during the early stages of bone formation. During this mineralization, hydroxyapatite (HA), a major component of bone, is synthesized, generating hard tissue. Many of the mechanisms driving biomineralization remain unclear because the traditional biochemical assays used to investigate them are destructive techniques incompatible with viable cells. To determine the temporal changes in mineralization-related biomolecules at mineralization spots, we performed time-lapse Raman imaging of mouse osteoblasts at a subcellular resolution throughout the mineralization process. Raman imaging enabled us to analyze the dynamics of the related biomolecules at mineralization spots throughout the entire process of mineralization. Here, we stimulated KUSA-A1 cells to differentiate into osteoblasts and conducted time-lapse Raman imaging on them every 4 hours for 24 hours, beginning 5 days after the stimulation. The HA and cytochrome c Raman bands were used as markers for osteoblastic mineralization and apoptosis. From the Raman images successfully acquired throughout the mineralization process, we found that β-carotene acts as a biomarker that indicates the initiation of osteoblastic mineralization. A fluctuation of cytochrome c concentration, which indicates cell apoptosis, was also observed during mineralization. We expect time-lapse Raman imaging to help us to further elucidate osteoblastic mineralization mechanisms that have previously been unobservable.

Clonal analysis of individual human embryonic stem cell differentiation patterns in microfluidic cultures

Heterogeneity in the clonal outputs of individual human embryonic stem cells (hESCs) confounds analysis of their properties in studies of bulk populations and how to manipulate them for clinical applications. To circumvent this problem we developed a microfluidic device that supports the robust generation of colonies derived from single ESCs. This microfluidic system contains 160 individually addressable chambers equipped for perfusion culture of individual hESCs that could be shown to match the growth rates, marker expression and colony morphologies obtained in conventional cultures. Use of this microfluidic device to analyze the clonal growth kinetics of multiple individual hESCs induced to differentiation revealed variable shifts in the growth rate, area per cell and expression of OCT4 in the progeny of individual hESCs. Interestingly, low OCT4 expression, a slower growth rate and low nuclear to cytoplasmic ratios were found to be correlated responses. This study demonstrates how microfluidic systems can be used to enable large scale live-cell imaging of isolated hESCs exposed to changing culture conditions, to examine how different aspects of their variable responses are correlated.

Raman spectroscopy for physiological investigations of tissues and cells

Raman micro-spectroscopy provides a convenient non-destructive and location-specific means of probing cellular physiology and tissue physiology at sub-micron length scales. By probing the vibrational signature of molecules and molecular groups, the distribution and metabolic products of small molecules that cannot be labeled with fluorescent dyes can be analyzed. This method works well for molecular concentrations in the micro-molar range and has been demonstrated as a valuable tool for monitoring drug-cell interactions. If the small molecule of interest does not contain groups that would allow for a discrimination against cytoplasmic background signals, "labeling" of the molecule by isotope substitution or by incorporating other unique small groups, e.g. alkynes provides a stable signal even for time-lapse imaging such compounds in living cells. In this review we highlight recent progress in assessing the physiology of cells and tissue by Raman spectroscopy and imaging.

Raman and autofluorescence spectrum dynamics along the HRG-induced differentiation pathway of MCF-7 cells

Cellular differentiation proceeds along complicated pathways, even when it is induced by extracellular signaling molecules. One of the major reasons for this complexity is the highly multidimensional internal dynamics of cells, which sometimes causes apparently stochastic responses in individual cells to extracellular stimuli. Therefore, to understand cell differentiation, it is necessary to monitor the internal dynamics of cells at single-cell resolution. Here, we used a Raman and autofluorescence spectrum analysis of single cells to detect dynamic changes in intracellular molecular components. MCF-7 cells are a human cancer-derived cell line that can be induced to differentiate into mammary-gland-like cells with the addition of heregulin (HRG) to the culture medium. We measured the spectra in the cytoplasm of MCF-7 cells during 12 days of HRG stimulation. The Raman scattering spectrum, which was the major component of the signal, changed with time. A multicomponent analysis of the Raman spectrum revealed that the dynamics of the major components of the intracellular molecules, including proteins and lipids, changed cyclically along the differentiation pathway. The background autofluorescence signals of Raman scattering also provided information about the differentiation process. Using the total information from the Raman and autofluorescence spectra, we were able to visualize the pathway of cell differentiation in the multicomponent phase space.

Identifying the lineages of individual cells in cocultures by multivariate analysis of Raman spectra

The cellular and matrix cues that induce stem cell differentiation into distinct cell lineages must be identified to permit the ex vivo expansion of desired cell populations for clinical applications. Combinatorial biomaterials enable screening multiple different microenvironments while using small numbers of rare stem cells. New methods to identify the phenotypes of individual cells in cocultures with location specificity would increase the efficiency and throughput of these screening platforms. Here, we demonstrate that partial least-squares discriminant analysis (PLS-DA) models of calibration Raman spectra from cells in pure cultures can be used to identify the lineages of individual cells in more complex culture environments. The calibration Raman spectra were collected from individual cells of four different lineages, and a PLS-DA model that captured the Raman spectral profiles characteristic of each cell line was created. The application of these models to Raman spectra from test sets of cells indicated individual, fixed and living cells in separate monocultures, as well as those in more complex culture environments, such as cocultures, could be identified with low error. Cells from populations with very similar biochemistries could also be identified with high accuracy. We show that these identifications are based on reproducible cell-related spectral features, and not spectral contributions from the culture environment. This work demonstrates that PLS-DA of Raman spectra acquired from pure monocultures provides an objective, noninvasive, and label-free approach for accurately identifying the lineages of individual, living cells in more complex coculture environments.

Development and integration of block operations for data invariant automation of digital preprocessing and analysis of biological and biomedical Raman spectra

High-throughput information extraction from large numbers of Raman spectra is becoming an increasingly taxing problem due to the proliferation of new applications enabled using advances in instrumentation. Fortunately, in many of these applications, the entire process can be automated, yielding reproducibly good results with significant time and cost savings. Information extraction consists of two stages, preprocessing and analysis. We focus here on the preprocessing stage, which typically involves several steps, such as calibration, background subtraction, baseline flattening, artifact removal, smoothing, and so on, before the resulting spectra can be further analyzed. Because the results of some of these steps can affect the performance of subsequent ones, attention must be given to the sequencing of steps, the compatibility of these sequences, and the propensity of each step to generate spectral distortions. We outline here important considerations to effect full automation of Raman spectral preprocessing: what is considered full automation; putative general principles to effect full automation; the proper sequencing of processing and analysis steps; conflicts and circularities arising from sequencing; and the need for, and approaches to, preprocessing quality control. These considerations are discussed and illustrated with biological and biomedical examples reflecting both successful and faulty preprocessing.