Zebrafish Tg(hb9:MTS-Kaede): a new in vivo tool for studying the axonal movement of mitochondria

ObjectivesDeregulation of axonal transport in neurons is emerging as the major cause of many neurodegenerative diseases in human, such as Charcot-Marie-Tooth (CMT) neuropathy. However, little is known about how mitochondria move in vivo and whether cell culture systems truly represent what happens in living animals. Here we describe the generation of a new zebrafish transgenic line that specifically allows to study mitochondrial dynamics in motor neurons and its application to analyse mitochondrial movement in zebrafish models expressing CMT2A causing mutations.MethodsThe Tol2 transposon system was used to generate a transgenic zebrafish line expressing the photoconvertible fluorescent protein Kaede in mitochondria of motor neurons. Mitochondrial shape and movement were monitored by time-lapse confocal live imaging and measured by kymograph analysis. The effects of two well-known CMT causing mutations, L76P and R94Q substitutions in MFN2, were then investigated with the same methods.ResultsWe generated the transgenic zebrafish Tg(hb9:MTS-Kaede) line with genetically labelled mitochondria in motor neurons. Kaede protein was correctly and stably targeted to mitochondrial matrix while retaining its photoconvertibility, thus qualifying this model for in vivo studies. Expression of the L76P and R94Q mutations reduced mitochondrial movement in axons and altered mitochondrial distribution in distinct ways.Conclusions and general significanceThese findings confirm previously published data obtained in cell cultures and strengthen the hypothesis of different mechanism of action of the two MFN2 mutations. Considering the number of neurodegenerative diseases associated to mitochondrial dynamics, the Tg(hb9:MTS-Kaede) zebrafish line is a promising model to study in vivo alterations of mitochondrial transport underlying human diseases.     

A Swiss family with hemoglobin P Galveston beta117His leads to Arg, including two patients with hb P/beta thalassemia.

The mutant Hb P Galveston (beta117His leads to Arg) is observed in two heterozygotes for beta thalassemia and by itself does not cause clinical symptoms. Some of the physico-chemical properties of Hb P Galveston are identical to the onemical properties of Hb P Galveston are identical to the ones hemoglobin Zurich (beta 63 His leads to Arg) so that only a detailed analysis led to its proper identification.     

Causality, randomness, intelligibility, and the epistemology of the cell

Because the basic unit of biology is the cell, biological knowledge is rooted in the epistemology of the cell, and because life is the salient characteristic of the cell, its epistemology must be centered on its livingness, not its constituent components. The organization and regulation of these components in the pursuit of life constitute the fundamental nature of the cell. Thus, regulation sits at the heart of biological knowledge of the cell and the extraordinary complexity of this regulation conditions the kind of knowledge that can be obtained, in particular, the representation and intelligibility of that knowledge. This paper is essentially split into two parts. The first part discusses the inadequacy of everyday intelligibility and intuition in science and the consequent need for scientific theories to be expressed mathematically without appeal to commonsense categories of understanding, such as causality. Having set the backdrop, the second part addresses biological knowledge. It briefly reviews modern scientific epistemology from a general perspective and then turns to the epistemology of the cell. In analogy with a multi-faceted factory, the cell utilizes a highly parallel distributed control system to maintain its organization and regulate its dynamical operation in the face of both internal and external changes. Hence, scientific knowledge is constituted by the mathematics of stochastic dynamical systems, which model the overall relational structure of the cell and how these structures evolve over time, stochasticity being a consequence of the need to ignore a large number of factors while modeling relatively few in an extremely complex environment.