Mitocheck
Mitocheck is an online molecular biology database created by the consortium of the same name . Funding came under the European sixth framework program for research and technological development (FP6, from 2002 to 2006). Mitocheck provides experimental data in the form of videos and graphics obtained from the culture of modified HeLa cells . One goal is to record the phenotypic characteristics of cell division ( mitosis ) of loss-of-function changes in this cell line for each individual gene in the human genome , to divide them into categories and thus to assign the possible function of the respective gene product ( protein ) in cell division determine. The work steps usually carried out for individual genes were automated and parallelized in this project, which is a novelty in such projects. Mitocheck was initially able to assign 600 genes, some of which were previously unknown, to cell division and, in a follow-up project, to identify 100 protein complexes .
Standard experiment
In order to determine the function of a gene product in HeLa cells during cell division, the respective gene is first “immobilized”. This is done by adding suitable siRNA to the cell culture . Ideally, this will attach to every mRNA molecule that is transcribed from the gene and prevent its further translation . No or only very little corresponding protein is thus produced. If this protein normally has an important function during cell division, this can be determined by looking at dividing cells under the microscope, especially if the cell's histones were stained with GFP . Missing enzymes or structural proteins can lead to changes in the process or complete defects in cell division.
Automation and parallelization
As part of the Mitocheck project, several automation steps were designed for the first time and initially tested in a pilot project with 49 genes.
RNA interference on microarrays
The microarray technology allows several hundred experiments to be carried out simultaneously. The Mitocheck project used self-generated RNA interference microarrays in which previously automatically synthesized siRNA was fixed on the individual (separated) positions and then covered with the cell culture. The siRNA then diffuses into the cells and binds to the appropriate mRNA.
Time-lapse microscopy
In order to follow all steps of cell division, it is apparently necessary to observe the cells for at least one cell division period. In order not only to automate this process, but also to parallelize it, Mitocheck developed a fluorescence microscope that was able to image the several hundred positions on a microarray at intervals of several minutes. The individual images of each position result in a time-lapse recording of what is happening. This is sufficient to determine changes compared to the norm and to divide them into categories.
Image processing through machine learning
To automate image processing, the Mitocheck project used methods commonly known as machine learning . Three problems had to be solved: the localization of individual chromosomes using a locally adaptive threshold value method , morphological classification of the chromosomes using previously manually trained support vector machines , and unsupervised phenotypic classification of the entire time-lapse recording using cluster analysis .
Results
The shutdown of about 21,000 genes produced about 190,000 time-lapse videos showing 19 million cell divisions. In the following, 1.9 billion cell nuclei were classified. A total of 1249 genes showed a deviation in cell division. In order to rule out false positives , a second run was carried out with 1,128 of these genes and altered siRNA, which ultimately resulted in 572 genes showing consistent results.
Individual evidence
- ↑ a b Neumann B, Walter T, Hériché JK, Bulkescher J, Erfle H, Conrad C, Rogers P, Poser I, Held M, Liebel U, Cetin C, Sieckmann F, Pau G, Kabbe1 R, Wünsche A, Satagopam V , Schmitz MHA, Chapuis C, Gerlich DW, Schneider R, Eils R, Huber W, Peters JM, Hyman AA, Durbin R, Pepperkok R and Ellenberg J: Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes . In: Nature . 464, April 2010, pp. 721-727. doi : 10.1038 / nature08869 .
- ↑ Hutchins JRA, Toyoda Y, Hegemann B, Poser I, Hériché JK, Sykora MM, Augsburg M, Hudecz O, Buschhorn BA, Bulkescher J, Conrad C, Comartin D, Schleiffer A, Sarov M, Pozniakovsky A, Slabicki MM, Schloissnig S, Steinmacher I, Leuschner M, Ssykor A, Lawo S, Pelletier L, Stark H, Nasmyth K, Ellenberg J, Durbin R, Buchholz F, Mechtler K, Hyman AA, Peters JM: Systematic Analysis of Human Protein Complexes Identifies Chromosome Segregation Protein . In: Science . April 2010. doi : 10.1126 / science.1181348 .
- ↑ Neumann B, Held M, Liebel U, et al. : High-throughput RNAi screening by time-lapse imaging of live human cells . In: Nat. Methods . 3, No. 5, May 2006, pp. 385-90. doi : 10.1038 / nmeth876 . PMID 16628209 .