EU funded research through three projects: MITOCHECK (‘ regulation of mitosis by phosphorylation: a multidisciplinary approach to Genomics Functional Proteomics and biology and chemistry), MITOSYS (systems biology of the mitotic) and MICROSCOPY SYSTEMS (microscopy systems: methodology key for next-generation systems biology.) Modern radiological techniques allow researchers to observe very complex processes at the cellular level. However, between the cells of a large sample, perhaps some are only in the process object of study, which is especially problematic when it comes to relatively unusual processes. To identify these cells, researchers should spend hours in front of the microscope, examining cells manually in search of those that interest them. This study describes an ingenious computer application which offers a solution to this problem. This efficient system, so-called Micropilot, examines samples in search of cells aim and subjected them to relevant experiments. It consists of a module based on the machine learning researchers can be ‘trained’ in a short time so that it automatically identify cells target. After entering the necessary information, Micropilot can explore the sample completely autonomously and in low resolution mode. When it identifies a cell that meets the needs of the researchers, the system happens to high-resolution scanning mode and automatically initiates more complex experiments.
It can be fairly simple tasks, as record video sequences accelerated at high resolution, or experiments of greater complexity, such as those involving the use of x-ray laser to manipulate marked proteins with a fluorescent reagent. The system requires a series of physical equipment such as a microscope with mobile stage that can automatically switch between objectives or change the zoom of the scanner laser, and change the filter of fluorescence and laser lines. The team tested this application in phases of the cell division cycle that occur relatively quickly and are therefore difficult to detect “in the Act”. Thanks to the Micropilot application, the team managed to detect the moment when form structures called sites of export from the endoplasmic reticulum (ERES) and sought information on the contribution of two proteins, CBX1 and CENP – E, to the process of condensation of the genetic material to form compact chromosomes and the formation of the spindle that allows you to align the chromosomes during cell division. The most fascinating feature of Micropilot is its speed: in just four nights in a fully autonomous activity, detected 232 cells on 2 specific stages of cell division and underwent a series of complex radiological experiments.
To an experienced microscopist you would have been at least one month of work on time complete to locate these cells among the thousands that make up a sample. Micropilot avoids the tedious task of manually generating repetitive data experts in cell biology, explained the team. You can accommodate virtually any radiological technique that enables automation and control online from the results of the classification of images using artificial vision. According to concluded the team, in three independent experimental initiatives, Micropilot allowed us perform a detailed statistical analysis of biological processes, making it a very useful tool for systems biology. Original author and source of the article.