Differential mitochondrial toxicity screening and multi-parametric data analysis.

Early evaluation of new drug entities for their potential to cause mitochondrial dysfunction is becoming an important task for drug development. Multi-parametric high-content screening (mp-HCS) of mitochondrial toxicity holds promise as a lead in-vitro strategy for drug testing and safety evaluations. In this study, we have developed a mp-HCS and multi-parametric data analysis scheme for assessing cell responses to induced mitochondrial perturbation. The mp-HCS measurements are shown to be robust enough to allow for quantitative comparison of biological systems with different metabolic pathways simulated by alteration of growth media. Substitution of medium glucose for galactose sensitized cells to drug action and revealed novel response parameters. Each compound was quantitatively characterized according to induced phenotypic changes of cell morphology and functionality measured by fluorescent biomarkers for mitochondrial activity, plasma membrane permeability, and nuclear morphology. Descriptors of drug effects were established by generation of a SCRIT (Specialized-Cell-Response-to-Induced-Toxicity) vector, consisting of normalized statistical measures of each parameter at each dose and growth condition. The dimensionality of SCRIT vectors depends on the number of parameters chosen, which in turn depends on the hypothesis being tested. Specifically, incorporation of three parameters of response into SCRIT vectors enabled clustering of 84 training compounds with known pharmacological and toxicological activities according to the degree of toxicity and mitochondrial involvement. Inclusion of 6 parameters enabled the resolution of more subtle differences between compounds within a common therapeutic class; scoring enabled a ranking of statins in direct agreement with clinical outcomes. Comparison of drug-induced changes required variations in glucose for separation of mitochondrial dysfunction from other types of cytotoxicity. These results also demonstrate that the number of drugs in a training set, the choice of parameters used in analysis, and statistical measures are fundamental for specific hypothesis testing and assessment of quantitative phenotypic differences.

Laminin assembles into separate basement membrane and fibrillar matrices in Schwann cells.

Laminins are important for Schwann cell basement membrane assembly and axonal function. In this study, we found that exogenous laminin-1, like neuromuscular laminins-2/4, formed two distinct extracellular matrices on Schwann cell surfaces, each facilitated by laminin polymerization. Assembly of one, a densely-distributed reticular matrix, was accompanied by a redistribution of cell-surface dystroglycan and cytoskeletal utrophin into matrix-receptor-cytoskeletal complexes. The other, a fibrillar matrix, accumulated in separate zones associated with pre-existing beta1-integrin arrays. The laminin-1 fragment E3 (LG-modules 4-5), which binds dystroglycan and heparin, inhibited reticular-matrix formation. By contrast, beta1-integrin blocking antibody (Ha2/5) prevented fibrillar assembly. Ultrastructural analysis revealed that laminin treatment induced the formation of a linear electron-dense extracellular matrix (lamina densa) separated from plasma membrane by a narrow lucent zone (lamina lucida). This structure was considerably reduced with non-polymerizing laminin, fully blocked by E3, and unaffected by Ha2/5. Although it formed in the absence of type IV collagen, it was nonetheless able to incorporate this collagen. Finally, cell competency to bind laminin and form a basement membrane was passage-dependent. We postulate that laminin induces the assembly of a basement membrane on competent cell surfaces probably mediated by anchorage through LG 4-5. Upon binding, laminin interacts with dystroglycan, mobilizes utrophin, and assembles a 'nascent' basement membrane, independent of integrin, that is completed by incorporation of type IV collagen. However, the fibrillar beta1-integrin dependent matrix is unlikely to be precursor to basement membrane.