MOSCOW, June 15. /TASS/ Scientists from Saint Petersburg University of Informational Technologies, Mechanics, and Optics (ITMO), the Federal Research and Clinical Centre of Physical-Chemical Medicine and MIPT have developed a software for analysis and comparison of DNA sets of microorganisms living in different environments. With the new algorithm, the microflora of a healthy person can be compared with the microflora of a patient, so that the previously unknown pathogenic microorganisms can be detected opening the route for developing aids for personalized medicine. The results of the study have been published in Bioinformatics. 

“In the microflora of a patient, it is possible to detect microorganisms associated with a particular disease, such as diabetes, or a predisposition to this disease. This already forms a basis for applying personalized medicine techniques and developing new drugs.”- comments Vladimir Ulyantsev, the lead developer of the algorithm and researcher at the Computer Technologies Laboratory at ITMO University. 

The newly developed software MetaFast is able to conduct a rapid comparative analysis of large amounts of metagenomes and to reveal pathogenic microorganisms without extraction and cultivation procedures. Metagenome is a collection of genes of all microorganisms living in a given environment, e.g. in a human bowel. Analyzing the metagenome, one could indicate various diseases or predispositions to such diseases. Therefore, studying microbiota, i.e. the full range of microorganisms inhabiting different parts of the human body, is of crucial importance in metagenomic research. 

The newly developed approach allows to find all possible genes even previously unknown ones and at the same time to identify metagenomic patterns that distinguish one patient from another, e.g. people with and without a disease. In the modern world, there is no database collecting all the microorganisms accosiated with particular diseases, hence the MetaFast could facilitate establishing such cause-and-effect relations. 

MetaFast is not limited to detecting pathogenic microorganisms. For example, the program can also be used to compare metagenomes of authentic people in closed populations with people living in cities to identify bacterial strains that are extremely useful to humans, but have been lost in the course of urbanization. The scientists have reported, that the MetaFast has demonstrated a high efficiency in studying rare and undiscovered metagenomes.

Nowadays, scientists from all over the world have already gathered a vast amount of experimental data on various metagenomes. This implies the particular importance of developing appropriate software for metagenome data analysis.