Shvetha Sankaran

Neural stem cell survival factors.

Neural stem and progenitor cells (NSCs and NPs) give rise to the central nervous system (CNS) during embryonic development. NSCs and NPs differentiate into three main cell-types of the CNS; astrocytes, oligodendrocytes, and neurons. NSCs are present in the adult CNS and are important in maintenance and repair. Adult NSCs hold great promise for endogenous or self-repair of the CNS. Intriguingly, NSCs have been implicated as the cells that give rise to brain tumors. Thus, the balance between survival, growth and differentiation is a critical aspect of NSC biology, during development, in the adult, and in disease processes. In this review, we survey what is known about survival factors that control both embryonic and adult NSCs. We discuss the neurosphere culture system as this is widely used to measure NSC activity and behavior in vitro and emphasize the importance of clonality. We define here NSC survival factors in their broadest sense to include any factor that influences survival and proliferation of NSCs and NPs. NSC survival factors identified to date include growth factors, morphogens, proteoglycans, cytokines, hormones, and neurotransmitters. Understanding NSC and NP interaction in response to these survival factors will provide insight to CNS development, disease and repair.

Single-cell mRNA profiling identifies progenitor subclasses in neurospheres.

Neurospheres are widely used to propagate and investigate neural stem cells (NSCs) and neural progenitors (NPs). However, the exact cell types present within neurospheres are still unknown. To identify cell types, we used single-cell mRNA profiling of 48 genes in 187 neurosphere cells. Using a clustering algorithm, we identified 3 discrete cell populations within neurospheres. One cell population [cluster unsorted (US) 1] expresses high Bmi1 and Hes5 and low Myc and Klf12. Cluster US2 shows intermediate expression of most of the genes analyzed. Cluster US3 expresses low Bmi1 and Hes5 and high Myc and Klf12. The mRNA profiles of these 3 cell populations correlate with a developmental timeline of early, intermediate, and late NPs, as seen in vivo from the mouse brain. We enriched the cell population for neurosphere-forming cells (NFCs) using morphological criteria of forward scatter (FSC) and side scatter (SSC). FSC/SSC(high) cells generated 2.29-fold more neurospheres than FSC/SSC(low) cells at clonal density. FSC/SSC(high) cells were enriched for NSCs and Lewis-X(+ve) cells, possessed higher phosphacan levels, and were of a larger cell size. Clustering of both FSC/SSC(high) and FSC/SSC(low) cells identified an NFC cluster. Significantly, the mRNA profile of the NFC cluster drew close resemblance to that of early NPs. Taken together, data suggest that the neurosphere culture system can be used to model central nervous system development, and that early NPs are the cell population that gives rise to neurospheres. In future work, it may be possible to further dissect the NFCs and reveal the molecular signature for NSCs.

Online 3-D Tracking of Suspension Living Cells Imaged with Phase-Contrast Microscopy

Neural stem cells/neural progenitors (NSCs/NPs) are cells that give rise to the main cell types of the nervous system: oligodendrocytes, neurons, and astrocytes. Studying NSCs/NPs with time-lapse microscopy is critical to the understanding of the biology of these cells. However, NSCs/NPs are very sensitive to phototoxic damage, and therefore, fluorescent dyes cannot be used to follow these cells. Also, since in most of NSC/NP-related experiments, a large number of cells neesd to be monitored. Consequently, the acquisition of a huge amount of images is required. An additional difficulty is related to our original suspension living, tracking objective, behavior much closer to the natural, in vivo, way of development of the cells. Indeed, unlike adherent cells, suspension cells float freely in a liquid solution, thus, making their dynamics very different from that of adherent cells. As a result, existing visual tracking algorithms that have primarily been developed to track adherent cells are no longer adequate to tackle living cells in suspension. This paper presents a novel automated 3-D visual tracking of suspension living cells for time-lapse image acquisition using phase-contrast microscopy. This new tracking method can potentially strongly impact on current 3-D video microscopy methods, paving the way for innovative analysis of NSCs/NPs and as a result, on the study of neurodegenerative diseases.

Purification, Visualization, and Molecular Signature of Neural Stem Cells

Neural stem cells (NSCs) are isolated from primary brain tissue and propagated as a heterogeneous mix of cells, including neural progenitors. To date, NSCs have not been purified in vitro to allow study of their biology and utility in regenerative medicine. In this study, we identify C1qR1as a novel marker for NSCs and show that it can be used along with Lewis-X (LeX) to yield a highly purified population of NSCs. Using time-lapse microscopy, we are able to follow NSCs forming neurospheres, allowing their visualization. Finally, using single-cell polymerase chain reaction (PCR), we determine the molecular signature of NSCs. The single-cell PCR data suggest that along with the Notch and Shh pathways, the Hippo pathway plays an important role in NSC activity.

A fluorescent probe for imaging symmetric and asymmetric cell division in neurosphere formation.

We report here a novel fluorescent chemical probe which stains distinct neural stem/progenitor cells (NSPCs) by binding to acid ceramidase in mouse neurospheres. is distributed evenly or unevenly to the daughter cells during multiple mitoses enabling the live imaging of symmetric and asymmetric divisions of isolated NSPCs.

Enumeration of Neural Stem Cells Using Clonal Assays

Neural stem cells (NSCs) have the ability to self-renew and generate the three major neural lineages — astrocytes, neurons and oligodendrocytes. NSCs and neural progenitors (NPs) are commonly cultured in vitro as neurospheres. This protocol describes in detail how to determine the NSC frequency in a given cell population under clonal conditions. The protocol begins with the seeding of the cells at a density that allows for the generation of clonal neurospheres. The neurospheres are then transferred to chambered coverslips and differentiated under clonal conditions in conditioned medium, which maximizes the differentiation potential of the neurospheres. Finally, the NSC frequency is calculated based on neurosphere formation and multipotency capabilities. Utilities of this protocol include the evaluation of candidate NSC markers, purification of NSCs, and the ability to distinguish NSCs from NPs. This method takes 13 days to perform, which is much shorter than current methods to enumerate NSC frequency.

Segmentation of neural stem cells/neurospheres in high content brightfield microscopy images using localized level sets

Neural stem cells and neural progenitors are early nervous system cells that form neurospheres when propagated in vitro. We study changes in growth using brightfield images to understand the effects of drugs. The image quality is generally poor, imposing challenges for automatic analysis. Level-set segmentation methods are able to handle topology changes but require close initializations for accurate and efficient results. Global level-set methods using single image-wide optimization objective functions are difficult to cope with large illumination and shading changes. We propose to adopt Hough transform to initialize localized level-sets for cell segmentation. Experimental results on 480 images with 738 neurospheres show that our proposed method performs best over existing level-set methods without appropriate initial contours.

A field theoretical restoration method for images degraded by non-uniform light attenuation : an application for light microscopy

Microscopy has become a de facto tool for biology. However, it suffers from a fundamental problem of poor contrast with increasing depth, as the illuminating light gets attenuated and scattered and hence can not penetrate through thick samples. The resulting decay of light intensity due to attenuation and scattering varies exponentially across the image. The classical space invariant deconvolution approaches alone are not suitable for the restoration of uneven illumination in microscopy images. In this paper, we present a novel physics-based field theoretical approach to solve the contrast degradation problem of light microscopy images. We have confirmed the effectiveness of our technique through simulations as well as through real field experimentations.

Neurosphere fate prediction: An analysis-synthesis approach for feature extraction

The study of stem cells is one of the current most important biomedical research field. Understanding their development could allow multiple applications in regenerative medicine. For this purpose, we need automated methods for the segmentation and the modeling of neural stem cell development process into a neurosphere colony from phase contrast microscopy. We use such methods to extract relevant structural and textural features like cell division dynamism and cell behavior patterns for biological interpretation. The combination of phase contrast imaging, high fragility and complex evolution of neural stem cells pose many challenges in image processing and image analysis. This study introduces an on-line analysis method for the modeling of neurosphere evolution during the first three days of their development. From the corresponding time-lapse sequences, we extract information from the neurosphere using a combination of fast level set and curve detection for segmenting the cells. Then, based on prior biological knowledge, we generate possible and optimal 3-dimensional configuration using registration and evolutionary optimisation algorithm.

Neurosphere segmentation in brightfield images

The challenge of segmenting neurospheres (NSPs) from brightfield images includes uneven background illumination (vignetting), low contrast and shadow-casting appearance near the well wall. We propose a pipeline for neurosphere segmentation in brightfield images, focusing on shadow-casting removal. Firstly, we remove vignetting by creating a synthetic blank field image from a set of brightfield images of the whole well. Then, radial line integration is proposed to remove the shadow-casting and therefore facilitate automatic segmentation. Furthermore, a weighted bi-directional decay function is introduced to prevent undesired gradient effect of line integration on NSPs without shadow-casting. Afterward, multiscale Laplacian of Gaussian (LoG) and localized region-based level set are used to detect the NSP boundaries. Experimental results show that our proposed radial line integration method (RLI) achieves higher detection accuracy over existing methods in terms of precision, recall and F-score with less computational time.