Time-lapse microscopy and classification of 2D human mesenchymal stem cells based on cell shape picks up myogenic from osteogenic and adipogenic differentiation

Current methods to characterize mesenchymal stem cells (MSCs) are limited to CD marker expression, plastic adherence and their ability to differentiate into adipogenic, osteogenic and chondrogenic precursors. It seems evident that stem cells undergoing differentiation should differ in many aspects, such as morphology and possibly also behaviour; however, such a correlation has not yet been exploited for fate prediction of MSCs. Primary human MSCs from bone marrow were expanded and pelleted to form high-density cultures and were then randomly divided into four groups to differentiate into adipogenic, osteogenic chondrogenic and myogenic progenitor cells. The cells were expanded as heterogeneous and tracked with time-lapse microscopy to record cell shape, using phase-contrast microscopy. The cells were segmented using a custom-made image-processing pipeline. Seven morphological features were extracted for each of the segmented cells. Statistical analysis was performed on the seven-dimensional feature vectors, using a tree-like classification method. Differentiation of cells was monitored with key marker genes and histology. Cells in differentiation media were expressing the key genes for each of the three pathways after 21 days, i.e. adipogenic, osteogenic and chondrogenic, which was also confirmed by histological staining. Time-lapse microscopy data were obtained and contained new evidence that two cell shape features, eccentricity and filopodia (= 'fingers') are highly informative to classify myogenic differentiation from all others. However, no robust classifiers could be identified for the other cell differentiation paths. The results suggest that non-invasive automated time-lapse microscopy could potentially be used to predict the stem cell fate of hMSCs for clinical application, based on morphology for earlier time-points. The classification is challenged by cell density, proliferation and possible unknown donor-specific factors, which affect the performance of morphology-based approaches. Copyright © 2012 John Wiley & Sons, Ltd.

Response to Innes and Mattsson: Neospora caninum emerges from the shadow of Toxoplasma gondii

It is tempting to extrapolate research findings regarding the intensively studied Toxoplasma gondii to Neospora caninum. This is based on morphological and ultrastructural studies, the molecular phylogeny of both parasites, their wide host ranges in nature, their ability to invade many different cell types in vitro and the occurrence of homologous proteins in both species. However, as Innes and Mattsson point out, T. gondii is the most successful parasite worldwide, whereas N. caninum has a more limited host range. Thus, some of the most challenging questions are: (i) what is T. gondii doing that N. caninum is not doing, or is doing differently, that renders the former so much more successful? And (ii) can some of these features be exploited for the development of interventional tools to limit infection and pathology caused by N. caninum?

Metabolites from intestinal microbes shape Treg

Intestinal bacterial metabolites are an important communication tool between the host immune system and the commensal microbiota to establish mutualism. In a recent paper published in Science, Wendy Garrett and her colleagues report an exciting role of the three most abundant microbial-derived short-chain fatty acids (SCFA), acetic acid, propionic acid and butyric acid, in colonic regulatory T cell (cTreg) homeostasis.

Stereological estimation of particle shape and orientation from volume tensors

In the present paper, we describe new robust methods of estimating cell shape and orientation in 3D from sections. The descriptors of 3D cell shape and orientation are based on volume tensors which are used to construct an ellipsoid, the Miles ellipsoid, approximating the average cell shape and orientation in 3D. The estimators of volume tensors are based on observations in several optical planes through sampled cells. This type of geometric sampling design is known as the optical rotator. The statistical behaviour of the estimator of the Miles ellipsoid is studied under a flexible model for 3D cell shape and orientation. In a simulation study, the lengths of the axes of the Miles ellipsoid can be estimated with CVs of about 2% if 100 cells are sampled. Finally, we illustrate the use of the developed methods in an example, involving neurons in the medial prefrontal cortex of rat.

Determination of Pelvic Orientation from Ultrasound Images Using Patch-SSMs and a Hierarchical Speed of Sound Compensation Strategy

In the field of computer assisted orthopedic surgery (CAOS) the anterior pelvic plane (APP) is a common concept to determine the pelvic orientation by digitizing distinct pelvic landmarks. As percutaneous palpation is - especially for obese patients - known to be error-prone, B-mode ultrasound (US) imaging could provide an alternative means. Several concepts of using ultrasound imaging to determine the APP landmarks have been introduced. In this paper we present a novel technique, which uses local patch statistical shape models (SSMs) and a hierarchical speed of sound compensation strategy for an accurate determination of the APP. These patches are independently matched and instantiated with respect to associated point clouds derived from the acquired ultrasound images. Potential inaccuracies due to the assumption of a constant speed of sound are compensated by an extended reconstruction scheme. We validated our method with in-vitro studies using a plastic bone covered with a soft-tissue simulation phantom and with a preliminary cadaver trial.

Validation of statistical shape model based reconstruction of the proximal femur - A morphology study

Seventeen bones (sixteen cadaveric bones and one plastic bone) were used to validate a method for reconstructing a surface model of the proximal femur from 2D X-ray radiographs and a statistical shape model that was constructed from thirty training surface models. Unlike previously introduced validation studies, where surface-based distance errors were used to evaluate the reconstruction accuracy, here we propose to use errors measured based on clinically relevant morphometric parameters. For this purpose, a program was developed to robustly extract those morphometric parameters from the thirty training surface models (training population), from the seventeen surface models reconstructed from X-ray radiographs, and from the seventeen ground truth surface models obtained either by a CT-scan reconstruction method or by a laser-scan reconstruction method. A statistical analysis was then performed to classify the seventeen test bones into two categories: normal cases and outliers. This classification step depends on the measured parameters of the particular test bone. In case all parameters of a test bone were covered by the training population's parameter ranges, this bone is classified as normal bone, otherwise as outlier bone. Our experimental results showed that statistically there was no significant difference between the morphometric parameters extracted from the reconstructed surface models of the normal cases and those extracted from the reconstructed surface models of the outliers. Therefore, our statistical shape model based reconstruction technique can be used to reconstruct not only the surface model of a normal bone but also that of an outlier bone.

Nanomechanics to drive stem cells in injured tissues: insights from current research and future perspectives

Stem cells reside within tissue, ensuring its natural ability to repair an injury. They are involved in the natural repair of damaged tissue, which encompasses a complex process requiring the modulation of cell survival, extracellular matrix turnover, angiogenesis, and reverse remodeling. To date, the real reparative potential of each tissue is underestimated and noncommittal. The assessment of the biophysical properties of the extracellular environment is an innovative approach to better understand mechanisms underlying stem cell function, and consequently to develop safe and effective therapeutic strategies replacing the loss of tissue. Recent studies have focused on the role played by biomechanical signals that drive stem cell death, differentiation, and paracrinicity in a genetic and/or an epigenetic manner. Mechanical stimuli acting on the shape can influence the biochemistry and gene expression of resident stem cells and, therefore, the magnitude of biological responses that promote the healing of injured tissue. Nanotechnologies have proven to be a revolutionary tool capable of dissecting the cellular mechanosensing apparatus, allowing the intercellular cross-talk to be decoded and enabling the reparative potential of tissue to be enhanced without manipulation of stem cells. This review highlights the most relevant findings of stem cell mechanobiology and presents a fascinating perspective in regenerative medicine.