Association of pellicle growth morphological characteristics and clinical presentation of Mycobacterium tuberculosis isolates

Trehalose dimycolate (TDM) is a mycobacterial glycolipid that is released from the surface of virulent M. tuberculosis. We evaluated the rate of growth, colony characteristics and production of TDM by Mycobacterium tuberculosis strains isolated from different clinical sites. Since detergent removes TDM from organisms, we analyzed growth rate and colony morphology of 79 primary clinical isolates grown as pellicles on the surface of detergent free Middlebrook 7H9 media. The genotype of each had been previously characterized. TDM production was measured by thin layer chromatography on 32 of these isolates. We found that strains isolated from pulmonary sites produced large amounts of TDM, grew rapidly as thin spreading pellicles, showed early cording (<1 week) and climbed the sides of the dish. In contrast, the extrapulmonary isolates (lymph node and bone marrow) produced less TDM (p<0.01), grew as discrete patches with little tendency to spread or climb the walls (p<0.02). The Beijing pulmonary (BP) isolates produced more TDM than non Beijing pulmonary isolates. The largest differences were observed in Beijing strains. The Beijing pulmonary isolates produced more TDM and grew faster than the Beijing extrapulmonary isolates (p<0.01). This was true even when the pulmonary and extrapulmonary isolates were derived from the same clade. These growth characteristics were consistently observed only on the first passage after primary isolation. This suggests that the differences in growth rate and TDM production observed reflect differences in gene expression patterns of pulmonary and extrapulmonary infections, that Mycobacterium tuberculosis in the lung grows more rapidly and produces more TDM than it does in extrapulmonary sites. This provides new opportunities to investigate gene expression of Mycobacterium tuberculosis in human.^

Computer simulation of glioma growth and morphology.

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

Computer simulation of glioma growth and morphology.

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

Predictive oncology: a review of multidisciplinary, multiscale in silico modeling linking phenotype, morphology and growth.

Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically assess advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we review a multiscale, i.e., from the molecular to the gross tumor scale, mathematical and computational "first-principle" approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We review the feasibility of this methodology that, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of tumor boundary can be inputted to the mathematical model and used as a phenotype-diagnostic tool to predict collective and individual tumor cell invasion of surrounding tissue. This approach further provides a means to deterministically test effects of novel and hypothetical therapy strategies on tumor behavior.

A pure population of lung alveolar epithelial type II cells derived from human embryonic stem cells.

Alveolar epithelial type II (ATII) cells are small, cuboidal cells that constitute approximately 60% of the pulmonary alveolar epithelium. These cells are crucial for repair of the injured alveolus by differentiating into alveolar epithelial type I cells. ATII cells derived from human ES (hES) cells are a promising source of cells that could be used therapeutically to treat distal lung diseases. We have developed a reliable transfection and culture procedure, which facilitates, via genetic selection, the differentiation of hES cells into an essentially pure (>99%) population of ATII cells (hES-ATII). Purity, as well as biological features and morphological characteristics of normal ATII cells, was demonstrated for the hES-ATII cells, including lamellar body formation, expression of surfactant proteins A, B, and C, alpha-1-antitrypsin, and the cystic fibrosis transmembrane conductance receptor, as well as the synthesis and secretion of complement proteins C3 and C5. Collectively, these data document the successful generation of a pure population of ATII cells derived from hES cells, providing a practical source of ATII cells to explore in disease models their potential in the regeneration and repair of the injured alveolus and in the therapeutic treatment of genetic diseases affecting the lung.

The type-A horizontal cell: GABAergic characteristics and role in development of the outer plexiform layer

Morphological analysis of neonatal rabbit retina suggests that the type-A horizontal cell acts as the pioneer cell for development of the OPL. It is the first mature element of the OPL, and it forms the infrastructure upon which the OPL accrues. The role of type-A horizontal cells in influencing postnatal development of the OPL was examined.^ GABAergic characteristics of the type-A horizontal cell were defined. The type-A horizontal cell was found to possess two more GABAergic characteristics in addition to those previously demonstrated, during a short period in early postnatal development: endogenous stores of GABA and the GABA precursor, glutamate. Lesioning the type-A horizontal cell resulted in their permanent loss in addition to the disappearance of cone terminals and a dramatic increase in rod terminals within the OPL. Thus the type-A cells are not a necessary prerequisite for positioning the OPL in postnatal development, but may be necessary for establishment of the normal photoreceptor mosaic.^ Since type-A horizontal cells possess a number of GABAergic qualities during the period of cone photoreceptor cell differentiation, and there are reports of GABA's trophic action in other developing neuronal systems; the role that GABAergic type-A horizontal cells play in directing photoreceptor differentiation was examined.^ Disrupting effects of GABA-A receptor antagonists indicate that type-A horizontal cells act as postsynaptic targets for the growing cone terminals of photoreceptor cells. These trophic or synaptic interactions may involve GABA-A receptors activated by GABA released from horizontal cells. These findings are consistent with the hypothesis that type-A horizontal cells act as pioneering cells in directing the postnatal development of the OPL.^ These studies offer an in depth analysis of the structural and chemical relationship between type-A horizontal cells and other elements of the OPL from which the roles of type-A horizontal cells and the GABA system in development can be defined. They contribute to our knowledge of both structural and GABAergic mechanisms involved in central nervous system development. ^