An exhaustive study with the participation of Sergi Valverde, researcher of the Complex Systems Lab at the Institute for Evolutionary Biology (IBE) UPF-CSIC mixed center published in the Journal Proceedings of the National Academy of Sciences, compiles the results of the research studies carried out in the last twenty years on viral infection of bacteria.

The group of the Georgia Institute of Technology (Atlanta, USA), with which the Catalan researcher has collaborated, has compiled data from 38 experiments, a total of 12,000 trials of infections which other groups have performed (and published) during the last twenty years. The work includes an experimental new study of one of the members of UPF's Complex Systems lab. Lab works in which experimental trials are done to understand which viruses infect which bacteria. As Valverde says "knowing who infects who is very useful to be able to develop future antimicrobial therapies".

A new computational technique to analyze infection matrices

Every experiment considered in the work gives rise to an infection matrix in which the columns are viruses which infect bacteria (fags) and the rows are infected bacteria or hosts. Therefore, the matrix indicates which bacteria are infected by which virus.

Sergi Valverde's contribution to this meta analysis has been to develop a new computational technique to detect regularities in the database containing the 38 matrices/experiments, as well as undertaking the analysis of part of the data, given that the Complex Systems Lab is a reference centre for the analysis and study of different kinds of complex networks.

Matrices reveal general principles of organization

The study has highlighted, firstly, that a wide body of viruses and bacteria have common infection patterns. As Valverde says, "these matrices show a high level of organization, that is, highly resistant bacteria are infected by generalist viruses, and bacteria which are easily infected are attacked both by generalist and specialist viruses". This suggests general principles of organization. Nevertheless, further experiments are needed to understand the origin of this common pattern.

Secondly, the study has shown that the networks theory allows doing algorithms which lead to discovering trends and general patterns in experimental databases. As Valverde comments "we expect that in the future, similar computational techniques will be used to analyze new experiments of bacteria infected by viruses".

Sergi Valverde is currently working as a post-doctoral researcher in the Complex Systems Lab, directed by Ricard Solé, ICREA researcher of the Experimental and Health Sciences Department of UPF, at the IBE (UPF-CSIC) and adjunct lecturer of mathematics on the Human Biology Degree in the Faculty of Life and Health Sciences of UPF.

This work is the result of international  collaboration that the IBE ( UPF-CSIC) has developed with the group led by Joshua Weitz of the Faculty of Biology of the Georgia Institute of Technology, Atlanta, (USA)