Accelerating Biodiversity Discovery in Hyperdiverse Arthropod Clades with Robots and Nanopore Sequencing


The biodiversity of arthropods remains poorly understood although it comprises much of the terrestrial animal biomass, most species, and supplies many ecosystem services. One obstacle is specimen-rich samples obtained with quantitative sampling techniques (e.g., Malaise trapping). Traditional “morpho-species” sorting requires too much time. At the Center of Integrative Biodiversity discovery at the Museum für Naturkunde in Berlin, we work on specimen-based approaches that pick individual specimen from bulk samples for barcoding. We developed a robot (“DiversityScanner”) that detects, images, and measures individual specimens and moves them into the wells of a 96-well microplate. The images are used to train convolutional neural networks (CNNs) that are capable of assigning the specimens to common 14 insect “families”. To obtain biomass information, the images are also used to measure specimen length and estimate body volume. In order to obtain DNA barcodes, we have developed robust and cost-effective barcoding techniques involving ONT sequencers and bioinformatics tools that allow for approximate species-level sorting.

Speaker's Profile:

Rudolf Meier is professor at Humboldt University. He received his PhD from Cornell University and was associate professor at the University of Copenhagen before moving to the National University of Singapore where he was professor at the Department of Biological Sciences. In 2020 he moved to Berlin to head the Center for integrative Biodiversity Discovery where new techniques for biodiversity discovery are developed. We combine Nanopore sequencing with robotics, and machine learning to accelerate biodiversity discovery, enable biodiversity monitoring, and discover species interactions.