Monitoring the environment with artificial intelligence
Microorganisms perform key functions in ecosystems, and their diversity reflects the health of their environment. However, they are still largely under-exploited in current biomonitoring programs because they are difficult to identify. Researchers from the University of Geneva (UNIGE), Switzerland, have recently developed an approach combining two cutting edge technologies to fill this gap. They used genomic tools to sequence the DNA of microorganisms in samples, and then exploited this considerable amount of data with artificial intelligence. They built predictive models capable of establishing a diagnosis of the health of ecosystems on a large scale, and identified species that perform important functions. This new approach, published in the journal Trends in Microbiology, will significantly increase the observation capacity of large ecosystems and reduce the time of analysis for very efficient routine biomonitoring programs.